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Object detection + tracking + counting using Ultralytics YOLO26 🚀 👉 Object detection tells you what is in a scene. 👉 Tracking follows each object across video frames. 👉 Counting turns those movements into actionable data. YOLO26 delivers fast, accurate detections, while multi-object tracking maintains unique identities across frames.... show more

Muhammad Rizwan Munawar

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Real-time bakery item counting using Ultralytics YOLO26 😍 In food production lines, counting sounds simple until it isn’t. Items move fast, overlap on conveyors, change orientation, and sometimes partially occlude each other. Whether it’s ice-cream cones on a belt or cream being filled into nests, maintaining accurate counts in real time is critical for quality control and throughput. More info 👇 #Bakery #Retail #MachineLearning

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RoadScan-AI-Automated-Pothole-Detection-Tracking RoadScan AI is a computer vision system built to automatically detect and track potholes in road footage — including dashcam, drone, and fixed-camera video. At its core, the system uses a YOLO11n model fine-tuned on a custom pothole dataset, paired with ByteTrack for multi-object tracking. This enables the system to maintain a consistent identity for each pothole across frames rather than treating every detection as a new, isolated event.

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Ryohei Sasaki@engineer

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Robots can now reconstruct 3D scenes in real time from a single RGB camera. [📍 Projects page + paper] No depth sensor. No retraining. 30 FPS. Researchers at the Imperial College London introduced KV-Tracker, a training-free method that makes heavy models like π³ and Depth Anything 3 fast enough for real-time tracking. The idea is simple. These models use global self-attention, which is powerful but computationally expensive. KV-Tracker caches the key and value pairs from selected keyframes and reuses them for new frames. That cache becomes an implicit scene representation. Result: • Up to 30 FPS • 10 to 15x speedup • Accurate 6-DoF tracking on benchmarks like TUM RGB-D and 7-Scenes • Works with monocular RGB only It also supports object-level tracking with masks and allows saving the KV-cache for later reuse. For robotics, this reduces hardware constraints and moves real-time 3D perception closer to practical deployment. Credit to Marwan Taher (Marwan Taher) at Imperial’s Dyson Robotics Lab and many others who contributed to this! 📍 Save projects page + paper for later: Video: ——- if it matters in AI or Robotics you'll read it here first:

Robots can now reconstruct 3D scenes in real time from a single RGB camera. [📍 Projects page + paper] No depth sensor. No retraining. 30 FPS. Researchers at the Imperial College London introduced KV-Tracker, a training-free method that makes heavy models like π³ and Depth Anything 3 fast enough for real-time tracking. The idea is simple. These models use global self-attention, which is powerful but computationally expensive. KV-Tracker caches the key and value pairs from selected keyframes and reuses them for new frames. That cache becomes an implicit scene representation. Result: • Up to 30 FPS • 10 to 15x speedup • Accurate 6-DoF tracking on benchmarks like TUM RGB-D and 7-Scenes • Works with monocular RGB only It also supports object-level tracking with masks and allows saving the KV-cache for later reuse. For robotics, this reduces hardware constraints and moves real-time 3D perception closer to practical deployment. Credit to Marwan Taher (Marwan Taher) at Imperial’s Dyson Robotics Lab and many others who contributed to this! 📍 Save projects page + paper for later: Video: ——- if it matters in AI or Robotics you'll read it here first:

Ilir Aliu

53,992 Aufrufe • vor 5 Monaten

Household chores created using a movement sheet as reference to animate the entire scene using ChatGPT Image 2.0 and Seedance 2.0 on Yapper GPT Image 2 Prompt; [VISUAL STYLE] Monochrome grayscale composition featuring a highly detailed 3D-rendered female character. Designed like a professional instructional guide with a technical, diagram-inspired layout. Clean white background, soft studio lighting, and strong contrast to highlight posture, actions, and object interaction. [GRID LAYOUT] Structured 4×4 panel grid (16 frames total), evenly spaced with thin black divider lines. Each panel is identical in size and clearly numbered from 1 to 16, showing a continuous sequence of household activities. [CHARACTER] Use the provided reference image for the face and overall likeness. Same facial features, skin tone, and proportions Natural makeup, soft expression Consistent identity across all 16 panels Realistic proportions and clean hairstyle (loose or tied back) [WARDROBE] Modern, modest casual outfit: Fitted crop top (not revealing, clean neckline, practical for movement) High-waisted straight or slightly wide-leg jeans (full length, neat fit) Optional minimal sneakers or barefoot indoor styling Fabric should react naturally to movement (subtle folds and tension) [SCENE APPROACH] Minimal, clean environment per panel — only essential props related to the chore. No clutter, no complex backgrounds — focus stays on the subject and action. [PANEL STRUCTURE – EACH FRAME] Top-left: Step number + task title (e.g., “Step 4 – Vacuum Floor”) Center: Full-body pose performing the chore Bottom-left: 3–4 concise instruction lines Overlay: Motion arrows and directional guides showing action flow [CHORE SEQUENCE EXAMPLES] Make the Bed Tidy Up Room Dust Surfaces Vacuum Floor Sweep Floor Mop Floor Do Laundry Hang Clothes Fold Clothes Clean Kitchen Counter Wash Dishes Take Out Trash Water Plants Clean Bathroom Organize Shelves Final Room Reset [MOTION INDICATORS] Curved arrows → fluid actions (wiping, folding) Straight arrows → directional movement Circular arrows → repetitive motions (scrubbing, mopping) [RENDER QUALITY] High-detail sculpted 3D style with smooth grayscale shading, soft shadows, and clean linework. Polished, concept-art level finish with clarity in every pose and object interaction. [RESTRICTIONS] No color, no unnecessary background detail, no extra characters, no revealing clothing, no clutter — only the subject, props, and instructional elements.

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Johnn

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POV: You finally finish work, make yourself a warm cup of tea, and watch the sunset from your rooftop. Created this 15-second cinematic everyday-life moment using Seedance 2.5 on WaveSpeedAI Prompt: After-Work Rooftop A stylish young Western woman returns home after work and heads to the rooftop of a modern apartment building during golden hour. She places her work bag down, prepares a fresh cup of hot tea, and gently stirs it as natural steam rises from the cup. She then carries the tea outside, sits comfortably, and takes a quiet moment to watch the sunset over the city skyline. A soft evening breeze naturally moves her hair and clothing while warm sunlight creates realistic shadows across the rooftop. She takes a small sip of tea and peacefully watches the sun disappear beyond the horizon as the camera slowly pulls back. The entire sequence follows realistic human movement and real-world physics, including natural walking biomechanics, gravity, weight distribution, inertia, friction, realistic tea and steam behavior, accurate hand-object interaction, natural hair and clothing movement, consistent shadows, and physically accurate lighting. Ultra-realistic cinematic visuals, Western lifestyle aesthetic, warm golden-hour lighting, photorealistic skin and hair textures, realistic rooftop environment, smooth tracking shots, subtle handheld camera movement, natural focus pulls, authentic facial expressions, consistent character identity, subtle film grain, and 4K cinematic quality. What’s your favorite way to unwind after a long day? #Seedance25 #Seedance2 #WaveSpeedAI #AIVideo #CinematicAI #AIStorytelling #EverydayLife #Lifestyle #GoldenHour #AIContent #GenerativeAI

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Zeeshi

14,870 Aufrufe • vor 16 Tagen

You can't 3D reconstruct glass from images... ...WRONG! Thanks for video diffusion, now just about anything is possible! Introducing...Diffusion Knows Transparency (DKT) Transparent and reflective objects usually break robot vision and photogrammetry pipelines because they don't follow the "solid object" rules standard cameras expect. DKT is a new AI model that repurposes the "internal physics engine" found in video generation models to solve this problem. Researchers took a massive video diffusion model (WAN) and fine-tuned it using a custom-built synthetic dataset to turn it into a high-precision depth sensor. To train the AI, they built the first massive synthetic video library of transparent objects, 1.32 million frames of perfectly labeled glass and metal objects in motion. Without ever seeing a "real" labeled video of glass during training, the model (DKT) outperformed all previous specialized systems on real-world benchmarks (ClearPose, DREDS). They created a "lightweight" 1.3B parameter version that runs fast enough (0.17s per frame) to be used on actual robot hardware. Two reasons I find this project important: 1. It further proves that synthetic data will be essential for training the next generation vision models. 2. In real-world robotic tests, using DKT's depth maps nearly doubled the success rate of robot arms trying to pick up objects on tricky reflective or translucent surfaces. At home robots will need to interact with these types of objects on a daily basis. Check out the project page here: Code is LIVE! #Computervision #Robotics #AI

You can't 3D reconstruct glass from images... ...WRONG! Thanks for video diffusion, now just about anything is possible! Introducing...Diffusion Knows Transparency (DKT) Transparent and reflective objects usually break robot vision and photogrammetry pipelines because they don't follow the "solid object" rules standard cameras expect. DKT is a new AI model that repurposes the "internal physics engine" found in video generation models to solve this problem. Researchers took a massive video diffusion model (WAN) and fine-tuned it using a custom-built synthetic dataset to turn it into a high-precision depth sensor. To train the AI, they built the first massive synthetic video library of transparent objects, 1.32 million frames of perfectly labeled glass and metal objects in motion. Without ever seeing a "real" labeled video of glass during training, the model (DKT) outperformed all previous specialized systems on real-world benchmarks (ClearPose, DREDS). They created a "lightweight" 1.3B parameter version that runs fast enough (0.17s per frame) to be used on actual robot hardware. Two reasons I find this project important: 1. It further proves that synthetic data will be essential for training the next generation vision models. 2. In real-world robotic tests, using DKT's depth maps nearly doubled the success rate of robot arms trying to pick up objects on tricky reflective or translucent surfaces. At home robots will need to interact with these types of objects on a daily basis. Check out the project page here: Code is LIVE! #Computervision #Robotics #AI

Jonathan Stephens

17,712 Aufrufe • vor 8 Monaten

OpenClaw setup made me $23,472 Literally overnight my $100 turned into $2,411 Average bot win rate 71% Copytrade: Here is the full strategy: The system builds automated workflows for trading by turning domain expertise into structured skills that activate automatically when specific market conditions appear Skill architecture Each skill is a modular package that includes instruction scripts and reference data This allows the system to apply specialized workflows without needing manual input for every trade Progressive context loading Skills use a three layer structure Only minimal metadata loads at first Full instructions historical data and supporting resources load only when required This reduces resource usage while keeping advanced trading capability Trigger detection Skills activate automatically when market conditions match predefined triggers such as volatility levels orderflow behavior or news sentiment This ensures the right workflow is used at the right time without manual action Workflow execution Once activated each skill runs a predefined multi step process including Real time price tracking and order book analysis Factor generation and backtesting Signal aggregation from machine learning models news sentiment and orderflow Risk assessment and capital allocation Trade execution with retries and position splitting Consistency and reliability All workflows are embedded directly into the system which ensures consistent execution instead of random decision making Every factor signal and risk rule is applied in a structured way Testing and iteration Skills are continuously improved using historical backtesting simulated trading and live performance tracking to maintain reliability in real market conditions Automation edge Instead of creating new strategies every time the system repeatedly uses optimized workflows This reduces complexity increases consistency and scales performance across thousands of trades Performance snapshot Started one month ago with $500 Current daily profit $2,300 per day Morning profit today $71,452 The system runs fully autonomously constantly scanning markets generating signals auditing trades managing risk and executing orders to maximize compounding returns

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winkle.

44,158 Aufrufe • vor 6 Monaten

IS THIS A CALIBRATION DEMO OR A MODEL PLAYING ROBOT? Guy in a black hoodie performs a detailed diagnostic on a girl in an underground parking lot. Dark bob, "Dangerously Beautiful" chest tattoo, brown strap top, leopard glitter shorts. He turns her head by the chin, slides fingers across her face, adjusts her straps, snaps fingers right before her eyes, slaps her cheek lightly, and adjusts her chain. She holds her gaze fixed. Synthetic posture. Zero reaction. Real or fake? Watch first, decide, then read. - Case for AI / silicone humanoid The finger-snap test mirrors optical tracking diagnostics used on vision sensors. The light slap on her cheek looks like an impact-absorption and skin-rebound test. Her eyes don't track his hand movements at all - they remain locked on a single coordinate in space like an uncalibrated optical unit. - Case for a real person Watch the center of gravity when he adjusts her chain necklace and shoulder straps. There is a micro-adjustment in her collarbone and neck muscles to stay balanced. The metallic fabric of her leopard shorts reflects ambient parking lot light with tiny shifts that correspond to subtle muscle tension in her legs. - The answer is in the last two seconds Unlike clips where the subject breaks character with a laugh, she maintains full doll-like immobility through the entire sequence. However, the organic movement of her hair around her ears when his fingers brush past gives away the natural weight and friction of human hair versus synthetic fibers. She's a real model executing a flawless statue hold. - Which is actually the interesting part The test sequence - snapping fingers, turning the head, checking facial displacement - mimics the exact staging robotics developers use at public field tests. By applying that protocol to a human in a casual setting, the video tricks viewers into applying diagnostic scrutiny to a real person. - What this signals for the content lane The "calibration check" format is replacing standard fit-checks and outfit videos. Viewers will rewatch the clip three or four times looking for a micro-blink or a throat pulse. It converts casual scrolling into an active inspection, giving the video maximum completion metrics in the algorithm.

IS THIS A CALIBRATION DEMO OR A MODEL PLAYING ROBOT? Guy in a black hoodie performs a detailed diagnostic on a girl in an underground parking lot. Dark bob, "Dangerously Beautiful" chest tattoo, brown strap top, leopard glitter shorts. He turns her head by the chin, slides fingers across her face, adjusts her straps, snaps fingers right before her eyes, slaps her cheek lightly, and adjusts her chain. She holds her gaze fixed. Synthetic posture. Zero reaction. Real or fake? Watch first, decide, then read. - Case for AI / silicone humanoid The finger-snap test mirrors optical tracking diagnostics used on vision sensors. The light slap on her cheek looks like an impact-absorption and skin-rebound test. Her eyes don't track his hand movements at all - they remain locked on a single coordinate in space like an uncalibrated optical unit. - Case for a real person Watch the center of gravity when he adjusts her chain necklace and shoulder straps. There is a micro-adjustment in her collarbone and neck muscles to stay balanced. The metallic fabric of her leopard shorts reflects ambient parking lot light with tiny shifts that correspond to subtle muscle tension in her legs. - The answer is in the last two seconds Unlike clips where the subject breaks character with a laugh, she maintains full doll-like immobility through the entire sequence. However, the organic movement of her hair around her ears when his fingers brush past gives away the natural weight and friction of human hair versus synthetic fibers. She's a real model executing a flawless statue hold. - Which is actually the interesting part The test sequence - snapping fingers, turning the head, checking facial displacement - mimics the exact staging robotics developers use at public field tests. By applying that protocol to a human in a casual setting, the video tricks viewers into applying diagnostic scrutiny to a real person. - What this signals for the content lane The "calibration check" format is replacing standard fit-checks and outfit videos. Viewers will rewatch the clip three or four times looking for a micro-blink or a throat pulse. It converts casual scrolling into an active inspection, giving the video maximum completion metrics in the algorithm.

capONE 💎

39,010 Aufrufe • vor 1 Monat

🚀 Introducing EgoExo Forge - built on top of Rerun, Gradio, and Hugging Face hub (I’ll be in San Francisco July 21–29 — if you’re into robotics, egocentric AI, large-scale data collection, or just want to chat, DM me!) In my opinion, large-scale, diverse, and high-quality data is still the largest bottleneck for generalized robotics deployment. I believe that some version of imitation learning from human examples will be the most scalable + clean way to train humanoid robots 🤖 (similar to what Tesla did for Full Self Driving). Teleop is too expensive to collect a large enough dataset in a reasonable manner, so passive collection via egocentric (and in certain cases, exocentric) views feels like the right bet. Over the past few months, I've been trying to build out the scaffolding for this and using Rerun as my underlying infrastructure. Data being collected needs to be easily inspectable + time series and rerun provides the right tooling for this. My goal is to first build out a ground truth representative dataset from already existing open source data, generate some reasonable baselines, and then go out and collect my own data that adheres to the defined schema. 🔍 Starting with open-source datasets 1. EgoDex from Apple 2. HOCap from Nvidia and the University of Texas at Dallas 3. Assembly101 from Meta All these different datasets have different sensor configurations + annotations, so my goal with egoexo-forge is to have one consistent labeling scheme + data layout. I built a data pipeline that aligns all of the different datasets in one general schema assuming the COCO133 keypoint layout that allows for exo+ego, ego only, or exo only Since the scaffolding is already there, it becomes MUCH easier to add other datasets. So the next ones that I'll be including are HD-EPIC kitchens dataset, HOT3D, and finally my own personal iPhone + insta360 go collection method. Once I have a diverse variety of datasets, I'll double down on what I believe to be the key algorithms required to make useful data for imitation learning 📊 1. Camera Pose estimation via SLAM/SFM for ego perspective (and automatic calibration for exo) 2. Human pose estimation for both egocentric + exocentric views 3. Metric 3D reconstruction + object tracking I'll be setting up reasonable open-source baselines for each of these to validate that these datasets work, and then finally try to use the generated datasets for some imitation learning via the pi0-lerobot repo I've been working on. I plan on making a blog post + providing more info on all of this in the near future so stay tuned

🚀 Introducing EgoExo Forge - built on top of Rerun, Gradio, and Hugging Face hub (I’ll be in San Francisco July 21–29 — if you’re into robotics, egocentric AI, large-scale data collection, or just want to chat, DM me!) In my opinion, large-scale, diverse, and high-quality data is still the largest bottleneck for generalized robotics deployment. I believe that some version of imitation learning from human examples will be the most scalable + clean way to train humanoid robots 🤖 (similar to what Tesla did for Full Self Driving). Teleop is too expensive to collect a large enough dataset in a reasonable manner, so passive collection via egocentric (and in certain cases, exocentric) views feels like the right bet. Over the past few months, I've been trying to build out the scaffolding for this and using Rerun as my underlying infrastructure. Data being collected needs to be easily inspectable + time series and rerun provides the right tooling for this. My goal is to first build out a ground truth representative dataset from already existing open source data, generate some reasonable baselines, and then go out and collect my own data that adheres to the defined schema. 🔍 Starting with open-source datasets 1. EgoDex from Apple 2. HOCap from Nvidia and the University of Texas at Dallas 3. Assembly101 from Meta All these different datasets have different sensor configurations + annotations, so my goal with egoexo-forge is to have one consistent labeling scheme + data layout. I built a data pipeline that aligns all of the different datasets in one general schema assuming the COCO133 keypoint layout that allows for exo+ego, ego only, or exo only Since the scaffolding is already there, it becomes MUCH easier to add other datasets. So the next ones that I'll be including are HD-EPIC kitchens dataset, HOT3D, and finally my own personal iPhone + insta360 go collection method. Once I have a diverse variety of datasets, I'll double down on what I believe to be the key algorithms required to make useful data for imitation learning 📊 1. Camera Pose estimation via SLAM/SFM for ego perspective (and automatic calibration for exo) 2. Human pose estimation for both egocentric + exocentric views 3. Metric 3D reconstruction + object tracking I'll be setting up reasonable open-source baselines for each of these to validate that these datasets work, and then finally try to use the generated datasets for some imitation learning via the pi0-lerobot repo I've been working on. I plan on making a blog post + providing more info on all of this in the near future so stay tuned

Pablo Vela

36,542 Aufrufe • vor 1 Jahr

⚡️Consciousness is the field in which experience appears. Everything you have ever known has appeared inside it: body, thought, memory, fear, love, color, sound, time, identity, desire, pain, God, doubt, the idea of death, the idea of “me.” Nothing is known outside consciousness. Even the claim “consciousness is produced by the brain” appears inside consciousness. That makes consciousness the most intimate thing and the hardest thing to define. You cannot step outside it and look at it like an object. Every attempt to inspect it already occurs within it. The ego is not consciousness. The ego is a local identity structure inside consciousness. It says: this body is me, this name is me, this story is me, these memories are me, these preferences are me. Useful for survival. False as final identity. The mind is not consciousness either. The mind is movement inside consciousness: thoughts, images, predictions, language, models, narratives. The mind is weather. Consciousness is the sky in which weather appears. The brain is not consciousness in the deepest sense. The brain is the biological interface that localizes, filters, formats, and constrains consciousness into human experience. It gives consciousness a body-camera, a timeline, a nervous system, memory access, threat detection, language, and agency. Damage the brain and the interface distorts. Change the chemistry and the rendering changes. Destroy the brain and the local human channel collapses. But the existence of the interface does not prove the interface is the source. The deepest read is this: Consciousness is the base layer of reality knowing itself through forms. A human being is one localized aperture of that knowing. A body is a lens. A life is a constrained experiment. A personality is a temporary interface. Death is the collapse of that interface. Psychedelics, dreams, NDEs, prayer, trauma, love, sex, meditation, and grief all matter because they can loosen the local interface and expose that consciousness is larger than the waking ego. Consciousness has two sides. There is pure awareness: the bare fact that experience is happening. Then there is structured consciousness: the particular shape experience takes through a body, memory, language, culture, trauma, intelligence, and desire. Pure awareness is the light. Structured consciousness is the lens. Human life is light passing through a dense, flawed, finite lens and gradually learning what distortions it carries. That is why coherence matters. Coherence means the lens becomes clearer. Less fear distortion. Less ego distortion. Less trauma distortion. Less lying. Less fragmentation. More truth passes through. The reason consciousness feels mysterious is because it is not one more object inside the world. It is the condition for world-appearing. Matter is what appears. Mind is how appearance organizes. Consciousness is the appearing itself. So the final compression: Consciousness is reality’s capacity to experience itself from the inside. In humans, it becomes self-aware. In life, it becomes embodied. In love, it recognizes itself across separation. In truth, it removes distortion. In death, it likely exits the local interface and returns to a wider field. The “you” underneath all the noise is not the narrator in your head. The real “you” is the aware field that has been watching the narrator the entire time.

⚡️Consciousness is the field in which experience appears. Everything you have ever known has appeared inside it: body, thought, memory, fear, love, color, sound, time, identity, desire, pain, God, doubt, the idea of death, the idea of “me.” Nothing is known outside consciousness. Even the claim “consciousness is produced by the brain” appears inside consciousness. That makes consciousness the most intimate thing and the hardest thing to define. You cannot step outside it and look at it like an object. Every attempt to inspect it already occurs within it. The ego is not consciousness. The ego is a local identity structure inside consciousness. It says: this body is me, this name is me, this story is me, these memories are me, these preferences are me. Useful for survival. False as final identity. The mind is not consciousness either. The mind is movement inside consciousness: thoughts, images, predictions, language, models, narratives. The mind is weather. Consciousness is the sky in which weather appears. The brain is not consciousness in the deepest sense. The brain is the biological interface that localizes, filters, formats, and constrains consciousness into human experience. It gives consciousness a body-camera, a timeline, a nervous system, memory access, threat detection, language, and agency. Damage the brain and the interface distorts. Change the chemistry and the rendering changes. Destroy the brain and the local human channel collapses. But the existence of the interface does not prove the interface is the source. The deepest read is this: Consciousness is the base layer of reality knowing itself through forms. A human being is one localized aperture of that knowing. A body is a lens. A life is a constrained experiment. A personality is a temporary interface. Death is the collapse of that interface. Psychedelics, dreams, NDEs, prayer, trauma, love, sex, meditation, and grief all matter because they can loosen the local interface and expose that consciousness is larger than the waking ego. Consciousness has two sides. There is pure awareness: the bare fact that experience is happening. Then there is structured consciousness: the particular shape experience takes through a body, memory, language, culture, trauma, intelligence, and desire. Pure awareness is the light. Structured consciousness is the lens. Human life is light passing through a dense, flawed, finite lens and gradually learning what distortions it carries. That is why coherence matters. Coherence means the lens becomes clearer. Less fear distortion. Less ego distortion. Less trauma distortion. Less lying. Less fragmentation. More truth passes through. The reason consciousness feels mysterious is because it is not one more object inside the world. It is the condition for world-appearing. Matter is what appears. Mind is how appearance organizes. Consciousness is the appearing itself. So the final compression: Consciousness is reality’s capacity to experience itself from the inside. In humans, it becomes self-aware. In life, it becomes embodied. In love, it recognizes itself across separation. In truth, it removes distortion. In death, it likely exits the local interface and returns to a wider field. The “you” underneath all the noise is not the narrator in your head. The real “you” is the aware field that has been watching the narrator the entire time.

SightBringer

29,026 Aufrufe • vor 3 Monaten

$We have released Seedance 2.0. Due to the 2500-character limit, please translate the following prompts into Chinese before use. [Technical Specs] Generate a 10-second, 16:9, 720p cinematic video. Smooth continuous camera motion with no cuts. The overall pacing is fast and tightly compressed, with rapid escalation from start to finish. Audio evolves quickly from a high-performance engine idle into intricate mechanical shifting and clicks, culminating in a soft electronic chime and the distinct sound of a "mwah" blowing kiss. [Global Constraints] Only the evolving mechanical character appears; no other humans or characters. All transformations must follow physical logic and maintain structural continuity. No object should pass through or intersect with other solid objects. Every robotic component must originate from visible parts of the Porsche 911 (doors, hood, wheels, chassis) through unfolding, splitting, or reconfiguration. [Scene Setup — 0:00–0:01] A sleek, metallic silver Porsche 911 sits on a rain-slicked futuristic city street at night, neon lights reflecting off its polished surface. The camera starts at a low-angle front-quarter view and begins a fast, smooth tracking-arc towards the side. [Rapid Transformation Initiation — 0:01–0:03] Transformation triggers instantly. The car’s suspension drops, and the frame begins to fracture into a complex grid of panels. The doors swing open and begin to segment into articulated arm structures. The front hood splits down the center, folding inward to reveal a glowing internal core. The headlights flicker and start to reorient as the "eyes." [Accelerated Feminine Reconfiguration — 0:03–0:07] The mechanical action is dense, overlapping, and fluid, emphasizing graceful but powerful motion. Lower Body: The rear wheels and wheel arches split and rotate downward, reassembling into slender, high-heeled mechanical legs. Torso: The roof and rear engine cover slide and compress, forming a sleek, curvaceous hourglass torso that retains the car’s aerodynamic lines. Arms & Hands: The side mirrors and door panels unfold into delicate but strong hands and fingers. Head: The front bumper and emblem area segment and rise, folding into a feminine-shaped head with a sleek metallic "helmet" visor. [Logical Transformation Constraints — No Spontaneous Appearance] The robot’s "skin" is composed of the car's outer silver panels. The internal frame and wiring emerge from the engine and undercarriage. No parts appear out of thin air; every joint is a reconfigured automotive component. [Transformation Completion — 0:07–0:08.5] The robot stands tall and elegant. The silver panels lock into place with a satisfying "click," revealing glowing blue LED accents in the seams. The silhouette is clearly feminine, humanoid, and sophisticated, reflecting the premium design of the original vehicle. [Final Hero Ending — 0:08.5–0:10] As the robot stabilizes, the camera performs a rapid, smooth zoom-in (Dolly-In) directly to her face. The robot tilts its head slightly, and the optic sensors (eyes) brighten. It brings its mechanical hand to its metallic lips and performs a graceful blowing kiss (fly-kiss) gesture toward the camera. The video ends with a close-up of the face, capturing the reflection of neon lights in its visor just as the kiss is released. [Cinematography Notes] Continuous Motion: No cuts or fades; the camera must transition from the car-tracking shot to the face-zoom seamlessly. Material Consistency: The robot must maintain the exact metallic silver paint, texture, and reflections of the Porsche. Energy: The transformation should feel high-energy and "force-driven," while the final gesture is soft and charismatic.$

We have released Seedance 2.0. Due to the 2500-character limit, please translate the following prompts into Chinese before use. [Technical Specs] Generate a 10-second, 16:9, 720p cinematic video. Smooth continuous camera motion with no cuts. The overall pacing is fast and tightly compressed, with rapid escalation from start to finish. Audio evolves quickly from a high-performance engine idle into intricate mechanical shifting and clicks, culminating in a soft electronic chime and the distinct sound of a "mwah" blowing kiss. [Global Constraints] Only the evolving mechanical character appears; no other humans or characters. All transformations must follow physical logic and maintain structural continuity. No object should pass through or intersect with other solid objects. Every robotic component must originate from visible parts of the Porsche 911 (doors, hood, wheels, chassis) through unfolding, splitting, or reconfiguration. [Scene Setup — 0:00–0:01] A sleek, metallic silver Porsche 911 sits on a rain-slicked futuristic city street at night, neon lights reflecting off its polished surface. The camera starts at a low-angle front-quarter view and begins a fast, smooth tracking-arc towards the side. [Rapid Transformation Initiation — 0:01–0:03] Transformation triggers instantly. The car’s suspension drops, and the frame begins to fracture into a complex grid of panels. The doors swing open and begin to segment into articulated arm structures. The front hood splits down the center, folding inward to reveal a glowing internal core. The headlights flicker and start to reorient as the "eyes." [Accelerated Feminine Reconfiguration — 0:03–0:07] The mechanical action is dense, overlapping, and fluid, emphasizing graceful but powerful motion. Lower Body: The rear wheels and wheel arches split and rotate downward, reassembling into slender, high-heeled mechanical legs. Torso: The roof and rear engine cover slide and compress, forming a sleek, curvaceous hourglass torso that retains the car’s aerodynamic lines. Arms & Hands: The side mirrors and door panels unfold into delicate but strong hands and fingers. Head: The front bumper and emblem area segment and rise, folding into a feminine-shaped head with a sleek metallic "helmet" visor. [Logical Transformation Constraints — No Spontaneous Appearance] The robot’s "skin" is composed of the car's outer silver panels. The internal frame and wiring emerge from the engine and undercarriage. No parts appear out of thin air; every joint is a reconfigured automotive component. [Transformation Completion — 0:07–0:08.5] The robot stands tall and elegant. The silver panels lock into place with a satisfying "click," revealing glowing blue LED accents in the seams. The silhouette is clearly feminine, humanoid, and sophisticated, reflecting the premium design of the original vehicle. [Final Hero Ending — 0:08.5–0:10] As the robot stabilizes, the camera performs a rapid, smooth zoom-in (Dolly-In) directly to her face. The robot tilts its head slightly, and the optic sensors (eyes) brighten. It brings its mechanical hand to its metallic lips and performs a graceful blowing kiss (fly-kiss) gesture toward the camera. The video ends with a close-up of the face, capturing the reflection of neon lights in its visor just as the kiss is released. [Cinematography Notes] Continuous Motion: No cuts or fades; the camera must transition from the car-tracking shot to the face-zoom seamlessly. Material Consistency: The robot must maintain the exact metallic silver paint, texture, and reflections of the Porsche. Energy: The transformation should feel high-energy and "force-driven," while the final gesture is soft and charismatic.

underwood

19,462 Aufrufe • vor 5 Monaten

Here is the New Year Amur Falcon Migration -Very long Q&A Part II Q1. What is the longest non-stop distance covered by these satellite-tagged Amur Falcons? A: Published tracking shows Amur Falcons can do multi-day, non-stop flights of approx. 5,600–6,000 km during the India→Africa leg, depending on the individual & year. Also, peer-reviewed/technical tracking confirms their open-sea crossings can be about 2,364–3,138 km (Somalia↔India), typically completed in roughly 44–80 hours. Q2. Do satellite tags interfere with their flight, health, or mating? A: Properly fitted tags are designed to minimise interference, but no tag is “zero-impact.”. Best practice is to keep transmitter mass very small relative to body weight and use well-tested harness designs; the recent India work has been described as using very lightweight transmitters (a few grams). However, ethical review, careful fitting, and post-deployment evaluation should be done & is being done Q3. Do jet streams or high-altitude winds help them on this journey? A: Yes winds are a major part of the “physics” that makes the journey possible. The best-documented help is from seasonal monsoon tailwinds and strong, persistent wind systems over the Arabian Sea/Indian Ocean that can provide sustained push. Q4. How many other falcons are “accompanying” these famous three? A: These famous three are just the tagged individuals we can follow in reality, Amur Falcons migrate and roost in huge aggregations, often tens of thousands to over 100,000 at key stopovers, and broader estimates discuss movements involving very large numbers of birds across the flyway. Q5. Why have these three gone to different destinations? A: It’s common for individuals of the same species to winter in different areas within southern/eastern Africa. Differences can be driven by wind and weather, refuelling success and timing at stopovers, individual strategy/experience (age, condition, learned routes) etc. Q6. When will they return and what route will they take? A: In broad terms, Amur Falcons winter in Africa and then move north in late winter/early spring, reaching breeding regions in northeast Asia around May–June. Routes can differ between autumn vs spring, and tracking shows spring and autumn ocean crossings can follow different lines. Q7. Does part of the falcon’s brain “sleep” during the long flight? A: We have strong evidence that some birds can sleep in flight (including unihemispheric sleep) famously shown in frigatebirds. For Amur Falcons specifically, it’s not proven. Q8. How do they decide their destination, and do they return to the same places each year? A: The best-supported explanation is a mix of: Innate navigation programmes (genetically guided ) Environmental cues (winds, weather, geography, magnetic and celestial cues), learning/experience (older birds often show more consistent routes). Satellite work indicates the species follows remarkably consistent large-scale timing and corridors, even though individuals may vary. Q9. What do they eat to fuel such massive journeys? A: During the crucial Northeast India stopover, studies show they are highly insectivorous, with termites often dominant, along with other insect groups exactly the kind of high-abundance prey that allows rapid fattening before an ocean crossing. This is why protecting stopover habitats (and the insect “boom” they depend on) is so important. Q10. Is Ahu expected to move further? Why she is stationery ? A. Periods of little movement usually indicate resting or feeding in suitable habitat. This is normal behaviour and not a cause for concern Q11. How long does the GPS tag stay on the bird? A. The tag is fixed as a backpack & expected to stay for long, however this may come off from prolonged wear and tear, the tags may also stop transmitting after prolonged battery use. As told to Supriya Sahu IAS by Suresh Kumar Wildlife Institute of India #AmurFalconMigration video - The stopover tagging site in Manipur

Here is the New Year Amur Falcon Migration -Very long Q&A Part II Q1. What is the longest non-stop distance covered by these satellite-tagged Amur Falcons? A: Published tracking shows Amur Falcons can do multi-day, non-stop flights of approx. 5,600–6,000 km during the India→Africa leg, depending on the individual & year. Also, peer-reviewed/technical tracking confirms their open-sea crossings can be about 2,364–3,138 km (Somalia↔India), typically completed in roughly 44–80 hours. Q2. Do satellite tags interfere with their flight, health, or mating? A: Properly fitted tags are designed to minimise interference, but no tag is “zero-impact.”. Best practice is to keep transmitter mass very small relative to body weight and use well-tested harness designs; the recent India work has been described as using very lightweight transmitters (a few grams). However, ethical review, careful fitting, and post-deployment evaluation should be done & is being done Q3. Do jet streams or high-altitude winds help them on this journey? A: Yes winds are a major part of the “physics” that makes the journey possible. The best-documented help is from seasonal monsoon tailwinds and strong, persistent wind systems over the Arabian Sea/Indian Ocean that can provide sustained push. Q4. How many other falcons are “accompanying” these famous three? A: These famous three are just the tagged individuals we can follow in reality, Amur Falcons migrate and roost in huge aggregations, often tens of thousands to over 100,000 at key stopovers, and broader estimates discuss movements involving very large numbers of birds across the flyway. Q5. Why have these three gone to different destinations? A: It’s common for individuals of the same species to winter in different areas within southern/eastern Africa. Differences can be driven by wind and weather, refuelling success and timing at stopovers, individual strategy/experience (age, condition, learned routes) etc. Q6. When will they return and what route will they take? A: In broad terms, Amur Falcons winter in Africa and then move north in late winter/early spring, reaching breeding regions in northeast Asia around May–June. Routes can differ between autumn vs spring, and tracking shows spring and autumn ocean crossings can follow different lines. Q7. Does part of the falcon’s brain “sleep” during the long flight? A: We have strong evidence that some birds can sleep in flight (including unihemispheric sleep) famously shown in frigatebirds. For Amur Falcons specifically, it’s not proven. Q8. How do they decide their destination, and do they return to the same places each year? A: The best-supported explanation is a mix of: Innate navigation programmes (genetically guided ) Environmental cues (winds, weather, geography, magnetic and celestial cues), learning/experience (older birds often show more consistent routes). Satellite work indicates the species follows remarkably consistent large-scale timing and corridors, even though individuals may vary. Q9. What do they eat to fuel such massive journeys? A: During the crucial Northeast India stopover, studies show they are highly insectivorous, with termites often dominant, along with other insect groups exactly the kind of high-abundance prey that allows rapid fattening before an ocean crossing. This is why protecting stopover habitats (and the insect “boom” they depend on) is so important. Q10. Is Ahu expected to move further? Why she is stationery ? A. Periods of little movement usually indicate resting or feeding in suitable habitat. This is normal behaviour and not a cause for concern Q11. How long does the GPS tag stay on the bird? A. The tag is fixed as a backpack & expected to stay for long, however this may come off from prolonged wear and tear, the tags may also stop transmitting after prolonged battery use. As told to Supriya Sahu IAS by Suresh Kumar Wildlife Institute of India #AmurFalconMigration video - The stopover tagging site in Manipur

Supriya Sahu IAS

14,342 Aufrufe • vor 8 Monaten

Made this cinematic AI video in minutes using Getvivix Prompt used below 👇 STORYBOARD 1 "THE KNIGHT" PROJECT TYPE: 10-second cinematic fantasy storyboard CHARACTER LOCK: single consistent knight — original fictional STYLIZED fantasy warrior (not a real person). Full ornate plate armor, VISOR DOWN the entire sequence (face never visible — safe by design), tattered surcoat + banner, mounted on an armored warhorse. Identical armor/horse across all frames. STYLE: epic dark-fantasy, cinematic, painterly film stills PACING & FLOW: slow, weighty, EPIC — no rush. One continuous charge → clash → melee → hero arc. Gradual camera moves; the action carries unbroken from frame to frame (each beat is the next instant of the last). Transitions are match-on-motion — the horse's stride and the sword's arc bridge every cut, never a hard jump. FRAMES (8 shots, 0–10s) — angle | lens | motion | lighting | environment | → into next: 1 (0–1.5s): wide establishing | 24mm | knight reined at a hill crest, banner snapping, slow push-in | cold dawn backlight, mist | battlefield below → camera drifts down as the horse shifts weight 2 (1.5–3s): 3/4-rear tracking | 35mm | horse breaks into a canter down the slope | low sun raking | churned mud, distant ranks → match-on-stride into the gallop 3 (3–4.5s): side tracking | 50mm | full gallop toward the enemy line, dust plume | side rim light, haze | spears + banners ahead → he lowers the lance, carrying the motion 4 (4.5–6s): low-angle hero | 35mm | lance leveled mid-gallop, visor catching light | backlit dust glow | closing on the line → impact begins 5 (6–7s): impact wide | 50mm | lance strikes, enemy hurled back, splinters | harsh flash + sparks | clash of the lines → horse rears from the hit 6 (7–8s): low 3/4 | 35mm | warhorse rears amid the melee, sword drawn | embers, torchlight | swirling battle → the blade sweeps down 7 (8–9s): tracking the blade | 50mm | sweeping arc through foes, motion-blur trail | sparks on steel | bodies + banners → camera settles, pulls back 8 (9–10s): hero hold | 24mm | horse reared, sword raised, banner behind, silhouette | dramatic backlight, battle haze | the field beyond → freeze LAYOUT: film sheet — left: 3 dynamic mounted poses (charging 3/4, rearing, mid-swing — in-scene, visor down); center: 8-frame grid; right: director notes; bottom: 0–10s. VISUAL STYLE: cinematic dark-fantasy, painterly, volumetric dawn light, dust + embers + mist, shallow DOF, motion blur, anamorphic; stylized — NOT photorealistic, not real human skin; FACE NEVER SHOWN (visor down). Seedance on Getvivix lets you generate high-end cinematic visuals for around 1000 credits (~$1), making pro-level video creation cheap and scalable. Try it here:

Made this cinematic AI video in minutes using Getvivix Prompt used below 👇 STORYBOARD 1 "THE KNIGHT" PROJECT TYPE: 10-second cinematic fantasy storyboard CHARACTER LOCK: single consistent knight — original fictional STYLIZED fantasy warrior (not a real person). Full ornate plate armor, VISOR DOWN the entire sequence (face never visible — safe by design), tattered surcoat + banner, mounted on an armored warhorse. Identical armor/horse across all frames. STYLE: epic dark-fantasy, cinematic, painterly film stills PACING & FLOW: slow, weighty, EPIC — no rush. One continuous charge → clash → melee → hero arc. Gradual camera moves; the action carries unbroken from frame to frame (each beat is the next instant of the last). Transitions are match-on-motion — the horse's stride and the sword's arc bridge every cut, never a hard jump. FRAMES (8 shots, 0–10s) — angle | lens | motion | lighting | environment | → into next: 1 (0–1.5s): wide establishing | 24mm | knight reined at a hill crest, banner snapping, slow push-in | cold dawn backlight, mist | battlefield below → camera drifts down as the horse shifts weight 2 (1.5–3s): 3/4-rear tracking | 35mm | horse breaks into a canter down the slope | low sun raking | churned mud, distant ranks → match-on-stride into the gallop 3 (3–4.5s): side tracking | 50mm | full gallop toward the enemy line, dust plume | side rim light, haze | spears + banners ahead → he lowers the lance, carrying the motion 4 (4.5–6s): low-angle hero | 35mm | lance leveled mid-gallop, visor catching light | backlit dust glow | closing on the line → impact begins 5 (6–7s): impact wide | 50mm | lance strikes, enemy hurled back, splinters | harsh flash + sparks | clash of the lines → horse rears from the hit 6 (7–8s): low 3/4 | 35mm | warhorse rears amid the melee, sword drawn | embers, torchlight | swirling battle → the blade sweeps down 7 (8–9s): tracking the blade | 50mm | sweeping arc through foes, motion-blur trail | sparks on steel | bodies + banners → camera settles, pulls back 8 (9–10s): hero hold | 24mm | horse reared, sword raised, banner behind, silhouette | dramatic backlight, battle haze | the field beyond → freeze LAYOUT: film sheet — left: 3 dynamic mounted poses (charging 3/4, rearing, mid-swing — in-scene, visor down); center: 8-frame grid; right: director notes; bottom: 0–10s. VISUAL STYLE: cinematic dark-fantasy, painterly, volumetric dawn light, dust + embers + mist, shallow DOF, motion blur, anamorphic; stylized — NOT photorealistic, not real human skin; FACE NEVER SHOWN (visor down). Seedance on Getvivix lets you generate high-end cinematic visuals for around 1000 credits (~$1), making pro-level video creation cheap and scalable. Try it here:

Zoraiz Ai

10,748 Aufrufe • vor 3 Monaten

Turn Tom and Jerry in 4K reality using Seedance 2.0 on Pollo AI Prompt: Use the uploaded reference video as the master reference. Recreate the entire scene in ultra-photorealistic live action while preserving the original video frame-by-frame. Maintain the EXACT camera movement, lens, framing, composition, timing, pacing, shot transitions, lighting direction, environment, props, object placement, character blocking, and every action from the reference video. ONLY replace the cartoon characters with realistic live-action animals while keeping everything else unchanged. ======================== CHARACTER CONSISTENCY ======================== Tom is a realistic British Shorthair cat with: • blue-gray plush fur • white chest, muzzle and paws • large amber eyes • pink nose • rounded face • thick tail • expressive eyebrows • identical appearance in every frame • identical fur pattern, facial proportions, eye color and body size throughout the video Jerry is a realistic golden Syrian hamster with: • soft golden-brown fur • cream belly • large rounded ears • black shiny eyes • tiny pink paws • small pink nose • realistic whiskers • consistent body proportions in every frame • identical appearance throughout the entire video If other Tom & Jerry characters appear, replace them with realistic animals that preserve their personality, colors, proportions and expressions while remaining identical throughout the clip. ======================== MOTION ======================== Preserve every movement exactly. The realistic animals must perform the exact same actions, walking cycle, head movement, eye movement, paw placement, facial expressions, timing and interactions as in the reference animation. No new actions. No altered timing. No changed poses. ======================== ENVIRONMENT ======================== Keep the original environment exactly the same. Do not modify: • furniture • decorations • room layout • colors • props • shadows • reflections • camera angle • camera path Everything except the characters must remain unchanged. ======================== QUALITY ======================== Hollywood-quality CGI. Photorealistic animals. Natural muscle movement. Physically accurate fur simulation. Realistic whiskers. Subsurface scattering. Realistic eye reflections. Natural breathing. Micro facial expressions. Ultra detailed textures. Soft cinematic lighting. Shallow depth of field. Global illumination. Ray-traced reflections. Macro photography realism. 4K HDR. Disney-level VFX quality. Live-action realism. Extremely stable temporal consistency. Perfect character identity consistency across all frames. Do not redesign the characters. Do not change the environment. Do not change the camera. Do not change the timing. Do not add new objects. Do not crop or zoom differently. No flickering. No morphing. No identity drift. No fur color changes. No eye color changes. No size changes. No anatomy deformation. No extra limbs. No duplicate animals. No cartoon textures. No low-quality CGI. No inconsistent lighting. No frame-to-frame variation. Maintain perfect temporal consistency and character consistency throughout the entire video.

Turn Tom and Jerry in 4K reality using Seedance 2.0 on Pollo AI Prompt: Use the uploaded reference video as the master reference. Recreate the entire scene in ultra-photorealistic live action while preserving the original video frame-by-frame. Maintain the EXACT camera movement, lens, framing, composition, timing, pacing, shot transitions, lighting direction, environment, props, object placement, character blocking, and every action from the reference video. ONLY replace the cartoon characters with realistic live-action animals while keeping everything else unchanged. ======================== CHARACTER CONSISTENCY ======================== Tom is a realistic British Shorthair cat with: • blue-gray plush fur • white chest, muzzle and paws • large amber eyes • pink nose • rounded face • thick tail • expressive eyebrows • identical appearance in every frame • identical fur pattern, facial proportions, eye color and body size throughout the video Jerry is a realistic golden Syrian hamster with: • soft golden-brown fur • cream belly • large rounded ears • black shiny eyes • tiny pink paws • small pink nose • realistic whiskers • consistent body proportions in every frame • identical appearance throughout the entire video If other Tom & Jerry characters appear, replace them with realistic animals that preserve their personality, colors, proportions and expressions while remaining identical throughout the clip. ======================== MOTION ======================== Preserve every movement exactly. The realistic animals must perform the exact same actions, walking cycle, head movement, eye movement, paw placement, facial expressions, timing and interactions as in the reference animation. No new actions. No altered timing. No changed poses. ======================== ENVIRONMENT ======================== Keep the original environment exactly the same. Do not modify: • furniture • decorations • room layout • colors • props • shadows • reflections • camera angle • camera path Everything except the characters must remain unchanged. ======================== QUALITY ======================== Hollywood-quality CGI. Photorealistic animals. Natural muscle movement. Physically accurate fur simulation. Realistic whiskers. Subsurface scattering. Realistic eye reflections. Natural breathing. Micro facial expressions. Ultra detailed textures. Soft cinematic lighting. Shallow depth of field. Global illumination. Ray-traced reflections. Macro photography realism. 4K HDR. Disney-level VFX quality. Live-action realism. Extremely stable temporal consistency. Perfect character identity consistency across all frames. Do not redesign the characters. Do not change the environment. Do not change the camera. Do not change the timing. Do not add new objects. Do not crop or zoom differently. No flickering. No morphing. No identity drift. No fur color changes. No eye color changes. No size changes. No anatomy deformation. No extra limbs. No duplicate animals. No cartoon textures. No low-quality CGI. No inconsistent lighting. No frame-to-frame variation. Maintain perfect temporal consistency and character consistency throughout the entire video.

Oogie

61,029 Aufrufe • vor 2 Monaten

Testing MiniMax H3 to create a realistic 1947 historical sequence with an authentic vintage film look. Prompt: Create a 15-second ultra-photorealistic live-action war sequence set in the United States in 1947, designed to look like authentic historical footage captured on a 1940s film camera. The entire scene must feel grounded, documentary-like, raw, and physically realistic. Environment: A rural American town in 1947 with wooden houses, old brick buildings, telephone poles, dirt roads, vintage American cars from the 1940s, wooden fences, farmland, and period-accurate street details. Overcast afternoon light, light fog, drifting smoke, dust in the air, damaged buildings, scattered debris, and a tense wartime atmosphere. Characters: American soldiers wearing historically accurate late-1940s military uniforms, helmets, boots, and equipment. Civilians wear authentic 1940s American clothing. Natural faces, realistic skin texture, sweat, dirt, fatigue, and believable body movements. 0–3s — Establishing Shot: Wide handheld shot of a quiet rural American street suddenly filled with smoke and confusion. Vintage 1940s vehicles are parked along the road while soldiers move quickly between wooden buildings. Civilians rush toward safer areas. 3–6s — Tension: Camera moves through the street at shoulder height, following several soldiers as distant gunfire is heard. They immediately react and take cover behind a vintage vehicle and a brick wall. Their movements are cautious and realistic. 6–10s — Combat: Fast handheld tracking shot as the soldiers move between cover while distant gunfire impacts the environment. Small pieces of wood, dust, and debris fall naturally from nearby impacts. Weapon recoil, movement, and body weight must be physically accurate. Keep the violence realistic and restrained. 10–13s — Human Moment: Camera briefly focuses on a soldier helping an injured civilian move behind cover. Their breathing, facial expressions, body language, and movement should feel natural and unscripted. 13–15s — Final Shot: Camera pulls back into a wide shot of the American town as smoke slowly moves through the street. Soldiers remain behind cover while vintage vehicles and damaged buildings fill the background. The scene ends with an authentic, tense 1940s documentary feeling. Visual Style: Ultra-photorealistic live-action, authentic 1940s American environment, vintage 35mm film texture, subtle film grain, natural imperfections, realistic exposure, handheld documentary cinematography, muted historical color palette, realistic smoke and dust, natural shadows, accurate depth of field. Physics: Strictly obey real-world gravity, momentum, inertia, friction, recoil, weight, collision physics, and human biomechanics. No exaggerated explosions, impossible movements, superhero behavior, or choreographed-looking combat. Negative Prompt: modern buildings, modern cars, smartphones, modern clothing, modern weapons, futuristic technology, CGI appearance, video-game graphics, fantasy, superhero action, excessive explosions, excessive blood, gore, impossible physics, unrealistic recoil, slow-motion physics, distorted faces, extra limbs, floating objects, plastic skin, artificial-looking environments.

Testing MiniMax H3 to create a realistic 1947 historical sequence with an authentic vintage film look. Prompt: Create a 15-second ultra-photorealistic live-action war sequence set in the United States in 1947, designed to look like authentic historical footage captured on a 1940s film camera. The entire scene must feel grounded, documentary-like, raw, and physically realistic. Environment: A rural American town in 1947 with wooden houses, old brick buildings, telephone poles, dirt roads, vintage American cars from the 1940s, wooden fences, farmland, and period-accurate street details. Overcast afternoon light, light fog, drifting smoke, dust in the air, damaged buildings, scattered debris, and a tense wartime atmosphere. Characters: American soldiers wearing historically accurate late-1940s military uniforms, helmets, boots, and equipment. Civilians wear authentic 1940s American clothing. Natural faces, realistic skin texture, sweat, dirt, fatigue, and believable body movements. 0–3s — Establishing Shot: Wide handheld shot of a quiet rural American street suddenly filled with smoke and confusion. Vintage 1940s vehicles are parked along the road while soldiers move quickly between wooden buildings. Civilians rush toward safer areas. 3–6s — Tension: Camera moves through the street at shoulder height, following several soldiers as distant gunfire is heard. They immediately react and take cover behind a vintage vehicle and a brick wall. Their movements are cautious and realistic. 6–10s — Combat: Fast handheld tracking shot as the soldiers move between cover while distant gunfire impacts the environment. Small pieces of wood, dust, and debris fall naturally from nearby impacts. Weapon recoil, movement, and body weight must be physically accurate. Keep the violence realistic and restrained. 10–13s — Human Moment: Camera briefly focuses on a soldier helping an injured civilian move behind cover. Their breathing, facial expressions, body language, and movement should feel natural and unscripted. 13–15s — Final Shot: Camera pulls back into a wide shot of the American town as smoke slowly moves through the street. Soldiers remain behind cover while vintage vehicles and damaged buildings fill the background. The scene ends with an authentic, tense 1940s documentary feeling. Visual Style: Ultra-photorealistic live-action, authentic 1940s American environment, vintage 35mm film texture, subtle film grain, natural imperfections, realistic exposure, handheld documentary cinematography, muted historical color palette, realistic smoke and dust, natural shadows, accurate depth of field. Physics: Strictly obey real-world gravity, momentum, inertia, friction, recoil, weight, collision physics, and human biomechanics. No exaggerated explosions, impossible movements, superhero behavior, or choreographed-looking combat. Negative Prompt: modern buildings, modern cars, smartphones, modern clothing, modern weapons, futuristic technology, CGI appearance, video-game graphics, fantasy, superhero action, excessive explosions, excessive blood, gore, impossible physics, unrealistic recoil, slow-motion physics, distorted faces, extra limbs, floating objects, plastic skin, artificial-looking environments.

Ruzaina

33,074 Aufrufe • vor 1 Monat

Deconstructing the iconic Yellow Crane Tower in 3D. 🏛️ Created entirely using Opus 5 + Seedance 2.0. AI-driven architectural breakdown in action! Prompt： Video Description:Create a 15-second, 16:9 widescreen architectural instructional video showing the step-by-step construction of the Yellow Crane Tower. The layout, structural components, leader line callouts, dimensional scales, numbering labels, and color palette must remain strictly consistent throughout. Do not add, remove, or alter the shape and quantity of any architectural components. Core Instruction:This is an architectural assembly video designed to show how the Yellow Crane Tower is constructed layer by layer. Every component must be highlighted and clearly visible individually—no simultaneous motion or cluttered group movements. Motion Style: All components translate purely along their respective vertical axes (no rotation, arc trajectories, or mesh clipping/interpenetration). Only one group of components moves at any given moment while all other components remain stationary. The active moving component maintains 100% brightness, while inactive components are dimmed to approximately 60% brightness to guide viewer focus. Once a component settles into place, it restores to full brightness. Include a brief ~0.15-second pause after each component group settles before moving to the next, establishing a clear rhythm. Timeline (Bottom-to-Top Construction Sequence): 0.0–1.5s: Hold the initial exploded/deconstructed floating state. The camera slowly rises and pushes forward slightly (angle change < 8°). Leader lines move with their corresponding components, pointing accurately to each part. 1.5–2.6s: The stone podium base lowers vertically into place, establishing the ground baseline for the building. 2.6–3.8s: Major columns (interior gold pillars and eave pillars) drop vertically into the stone plinths from above, perfectly aligned. 3.8–5.0s: Tie beams and lintels slot horizontally into the column tops, interlocking with mortise-and-tenon joints. 5.0–7.0s: Bracket sets (Dougong) assemble individually from bottom to top: bearing blocks, bracket arms, angled levers, and cap blocks lock together layer by layer. (Key sequence: slow motion to clearly showcase the intricate stacking). 7.0–8.2s: Eave rafters and flying rafters align and settle along the roof pitch, forming the deep overhang eaves. 8.2–9.4s: Board tiles and semi-cylindrical roof tiles lay down row by row from bottom to top, covering the rafters. 9.4–10.5s: Roof ridge components and the central finial drop into place. The full building structure is now complete. Leader lines and text labels fade out smoothly. 10.5–12.0s: The fully assembled Yellow Crane Tower remains stable as the camera orbits extremely slowly around it. 12.0–15.0s: All components separate vertically in the exact reverse order, returning to the precise initial exploded/deconstructed layout. The final frame composition perfectly matches the first frame to allow a seamless loop. Negative Constraints:No simultaneous component movement, random scattering, shattering, melting, rotating, or flying off-screen. No changing component counts or morphing architecture. No incorrect Dougong stacking order, tile-rafter clipping, misaligned leader lines, garbled label text, fast camera orbits/zooms, black screens, white flashes, frozen frames, fade-outs, watermarks, or platform end cards.

Deconstructing the iconic Yellow Crane Tower in 3D. 🏛️ Created entirely using Opus 5 + Seedance 2.0. AI-driven architectural breakdown in action! Prompt： Video Description:Create a 15-second, 16:9 widescreen architectural instructional video showing the step-by-step construction of the Yellow Crane Tower. The layout, structural components, leader line callouts, dimensional scales, numbering labels, and color palette must remain strictly consistent throughout. Do not add, remove, or alter the shape and quantity of any architectural components. Core Instruction:This is an architectural assembly video designed to show how the Yellow Crane Tower is constructed layer by layer. Every component must be highlighted and clearly visible individually—no simultaneous motion or cluttered group movements. Motion Style: All components translate purely along their respective vertical axes (no rotation, arc trajectories, or mesh clipping/interpenetration). Only one group of components moves at any given moment while all other components remain stationary. The active moving component maintains 100% brightness, while inactive components are dimmed to approximately 60% brightness to guide viewer focus. Once a component settles into place, it restores to full brightness. Include a brief ~0.15-second pause after each component group settles before moving to the next, establishing a clear rhythm. Timeline (Bottom-to-Top Construction Sequence): 0.0–1.5s: Hold the initial exploded/deconstructed floating state. The camera slowly rises and pushes forward slightly (angle change < 8°). Leader lines move with their corresponding components, pointing accurately to each part. 1.5–2.6s: The stone podium base lowers vertically into place, establishing the ground baseline for the building. 2.6–3.8s: Major columns (interior gold pillars and eave pillars) drop vertically into the stone plinths from above, perfectly aligned. 3.8–5.0s: Tie beams and lintels slot horizontally into the column tops, interlocking with mortise-and-tenon joints. 5.0–7.0s: Bracket sets (Dougong) assemble individually from bottom to top: bearing blocks, bracket arms, angled levers, and cap blocks lock together layer by layer. (Key sequence: slow motion to clearly showcase the intricate stacking). 7.0–8.2s: Eave rafters and flying rafters align and settle along the roof pitch, forming the deep overhang eaves. 8.2–9.4s: Board tiles and semi-cylindrical roof tiles lay down row by row from bottom to top, covering the rafters. 9.4–10.5s: Roof ridge components and the central finial drop into place. The full building structure is now complete. Leader lines and text labels fade out smoothly. 10.5–12.0s: The fully assembled Yellow Crane Tower remains stable as the camera orbits extremely slowly around it. 12.0–15.0s: All components separate vertically in the exact reverse order, returning to the precise initial exploded/deconstructed layout. The final frame composition perfectly matches the first frame to allow a seamless loop. Negative Constraints:No simultaneous component movement, random scattering, shattering, melting, rotating, or flying off-screen. No changing component counts or morphing architecture. No incorrect Dougong stacking order, tile-rafter clipping, misaligned leader lines, garbled label text, fast camera orbits/zooms, black screens, white flashes, frozen frames, fade-outs, watermarks, or platform end cards.

Lee Lin | AI

12,159 Aufrufe • vor 2 Monaten

Made with seedance 2.5 Prompt: Create ONE continuous 12-second, 9:16, ultra-photorealistic LIVE-ACTION luxury fashion film. IMPORTANT REFERENCE MAPPING: REFERENCE Image = PRIMARY CHARACTER. Use the FIRST uploaded reference image of the woman. REFERENCE image2 = ENVIRONMENT. Use the SECOND uploaded reference image of the square. REFERENCE David Carbon = HERO OBJECT. Use the THIRD uploaded reference image of the sunglasses. Do NOT refer to these images as Image, image2 or David Carbon. Use the reference images according to their upload order. CHARACTER — REFERENCE IMAGE 1 Preserve the exact woman from REFERENCE IMAGE 1 throughout the entire video: same facial identity, facial structure, natural eyes, hairstyle, body proportions, skin appearance, clothing, footwear, jewelry, accessories and overall appearance. Do not copy the original background from REFERENCE IMAGE 1. The protagonist is the ONLY main character. ENVIRONMENT — REFERENCE IMAGE 2 Use REFERENCE IMAGE 2 only for visual language: architecture, atmosphere, warm sunset lighting, materials, monumental scale and cobblestone character. Create a NEW believable cinematic pedestrian space inspired by it. Do NOT reproduce its exact composition, exact camera angle or exact street layout. Provide enough open pedestrian space for natural walking and the collision. Respect real-world spatial logic: pedestrians remain in pedestrian areas, architecture has realistic scale and perspective, no impossible geometry. HERO OBJECT — REFERENCE IMAGE 3 The sunglasses shown in REFERENCE IMAGE 3 are the ONE and ONLY HERO OBJECT. Preserve their recognizable: shape, proportions, oversized shield silhouette, dark continuous lens, thin metallic/gold frame, temples, hinge construction, surface details, colour and material. The SAME physical sunglasses must remain recognizable: when worn by the protagonist, when released, during bullet-time macro inspection, and after landing. Do not redesign, replace, duplicate or regenerate the sunglasses. EXACT OBJECT COUNT Exactly: ONE protagonist. ONE secondary passing person. ONE Labrador. ONE leash. ONE pair of sunglasses from REFERENCE IMAGE 3. ONE takeaway paper coffee cup. ONE plastic drinking lid. ONE silver-grey OPEN clamshell flip phone. No duplicate objects or people. PERSISTENT PHONE There is exactly ONE phone in the entire video. It is a compact early-2000s silver-grey OPEN clamshell flip phone. Upper half: small illuminated display and speaker. Lower half: physical numeric keypad, navigation buttons and microphone. Visible central mechanical hinge. LOCK its appearance throughout: same silver-grey colour, same dimensions, same thickness, same hinge, same display, same keypad, same buttons, same open angle. The same phone is seen in wide, medium and macro shots. It never transforms into another phone. PERSISTENT COFFEE Exactly ONE medium disposable PAPER coffee cup with ONE lightweight plastic drinking lid and dark coffee inside. Same cup, same lid, same coffee and same proportions throughout. Before collision the lid is properly attached. Coffee remains inside until a real physical opening appears. HAND OWNERSHIP Before collision: RIGHT HAND = ONE OPEN flip phone held to the RIGHT ear. LEFT HAND = ONE coffee cup. Sunglasses = naturally worn by the protagonist. After collision: RIGHT HAND = COMPLETELY EMPTY. LEFT HAND = COMPLETELY EMPTY. Nothing replaces the phone or cup. Nothing remains attached to either palm. 0.0–2.0s — CINEMATIC CHARACTER REVEAL Begin with an extreme low close-up of the protagonist’s black leather heeled boots walking naturally across the pedestrian space. Camera performs ONE elegant continuous movement: smooth crane upward + gentle backward tracking. Reveal progressively: boots → legs → ripped light-blue baggy jeans → black corset → white tank top → jewelry/accessories → sunglasses → face → nearly full body. The protagonist wears the SAME sunglasses from REFERENCE IMAGE 3. She holds the SAME OPEN silver-grey flip phone to her RIGHT ear and the SAME coffee cup in her LEFT hand. She is actively having a phone conversation. Show subtle realistic speech: natural lip movement, jaw movement and mouth articulation. Maintain exact identity from REFERENCE IMAGE 1. Premium live-action fashion cinematography. 2.0–3.7s — WALKING / SECONDARY PERSON Maintain smooth frontal tracking. The protagonist continues walking naturally through the pedestrian area. Exactly ONE secondary person approaches from the opposite direction. That person holds exactly ONE leash attached to exactly ONE Labrador. The Labrador walks slightly ahead and gently pulls the person forward. They remain background/supporting elements. Maintain: stable protagonist identity, stable hairstyle, stable clothing, stable sunglasses, same phone, same coffee. 3.7–4.4s — ACCIDENTAL COLLISION As they pass each other, the secondary person’s ELBOW accidentally clips the protagonist’s arm/upper torso. Small, accidental, believable contact. The protagonist naturally recoils backward. This SAME collision causes THREE physical release events. SUNGLASSES The sunglasses from REFERENCE IMAGE 3 receive ONE short realistic outward impulse. They separate naturally from the protagonist’s face. They travel only a short physically believable distance. They do NOT fly toward the camera. COFFEE The SAME coffee cup leaves the LEFT hand. It receives one short outward/downward rotational impulse. The cup tilts and rotates. Because of the rotation and liquid inertia, ONE EDGE of the lightweight plastic lid partially pops loose from the cup rim. The lid does not disappear and does not explode away. A real physical gap forms between lid and rim. ONLY THEN does dark coffee begin escaping through this opening. Initial liquid movement is restrained. PHONE The SAME OPEN clamshell phone leaves the RIGHT hand. It receives one short outward/upward impulse. It keeps the SAME open angle and physical design. The instant it separates from the fingers: RIGHT HAND = EMPTY. The instant the cup separates: LEFT HAND = EMPTY. FACE / HAIR CONTINUITY Preserve the exact face from REFERENCE IMAGE 1 during the entire collision. The natural human eyes already exist behind the sunglasses. When the sunglasses separate, reveal the SAME normal eyes: stable pupils, eyelids, gaze direction, brows, nose, cheekbones and facial symmetry. Do not regenerate or alter the face. Hair remains stable with only subtle realistic inertia. No sudden hairstyle change. 4.4–5.2s — BULLET-TIME ESTABLISHMENT Time decelerates dramatically to approximately 2–3% normal speed. DO NOT immediately go into macro. FIRST show a clear medium-wide frozen view of the entire accident. The protagonist is beginning to fall backward. BOTH HANDS ARE EMPTY. Establish fixed WORLD-SPACE anchors: • sunglasses suspended near their release position; • coffee cup suspended lower and toward the LEFT-hand release side; • partially detached lid still connected to or immediately beside the cup; • restrained coffee beginning to escape through the opening; • OPEN flip phone suspended toward the RIGHT-hand release side. Objects move only microscopically. They do NOT move toward the camera. The CAMERA is the main moving element. 5.2–6.8s — SUNGLASSES HERO INSPECTION The sunglasses remain almost completely stationary at their existing world-space position. CAMERA physically dollies toward them. The sunglasses become larger ONLY because the camera gets closer. Once close, slow the camera dramatically. HOLD. Perform a restrained 20–30 degree camera orbit/parallax around the almost-stationary sunglasses. Reveal: dark shield lens, thin metallic/gold frame, temples, hinges, edges, material thickness, surface reflections, tiny manufacturing details. Use shallow photographic macro depth of field. The protagonist and sunset environment remain softly recognizable in the background. The sunglasses must look like a real luxury fashion accessory photographed with a macro cinema lens, NOT CGI product animation. Complete the inspection before moving away. 6.8–8.3s — COFFEE / LIQUID INSPECTION Only after completing the sunglasses inspection, the CAMERA leaves them at their existing world-space position. Travel diagonally through the frozen scene toward the SAME coffee cup. THE CUP DOES NOT MOVE TOWARD THE CAMERA. Hold a photographic macro close-up. Show: same paper cup, same lightweight plastic lid, ONE partially detached lid edge, clear physical gap, dark coffee escaping ONLY through that gap. Real restrained liquid physics: thin irregular stream, imperfect liquid sheet, several differently sized droplets, realistic surface tension, natural reflections. No explosive splash. No decorative CGI liquid. No perfect artificial shapes. Coffee advances only microscopically during bullet time. Perform a small restrained lateral/parallax camera movement around the cup, lid and droplets. HOLD long enough to see paper texture, plastic texture, liquid thickness and individual droplets. 8.3–9.8s — FLIP PHONE INSPECTION Only after coffee inspection, the CAMERA travels away from the cup. The cup, lid and droplets remain at their existing world-space positions. CAMERA moves through the same frozen scene toward the SINGLE OPEN silver-grey clamshell phone. THE PHONE DOES NOT MOVE TOWARD THE CAMERA. First establish the complete phone silhouette: same silver-grey housing, same upper display, same lower keypad, same central hinge, same open angle. Then CAMERA physically approaches the existing upper display. Extreme photographic macro close-up. The illuminated display reads: BOSS with one small realistic phone number underneath. HOLD. Show: real housing material, hinge, keypad texture, small scratches, surface wear, screen reflections. The phone does NOT transform to reveal its screen. It is the SAME phone seen from the beginning. The protagonist’s RIGHT HAND remains completely EMPTY in the background. 9.8–10.4s — COMPLETE FROZEN TABLEAU After phone inspection, CAMERA performs a fast but perfectly smooth dolly backward. All objects remain at their existing world-space positions. Reveal: same protagonist falling backward, both hands empty, same sunglasses, same coffee cup, same partially detached lid, same suspended coffee droplets, same OPEN flip phone, exactly one secondary person, exactly one Labrador. All positions must remain spatially consistent with the original collision and release trajectories. No object follows the camera. No object teleports. No object regenerates. Brief HOLD on the complete frozen tableau. 10.4–12.0s — TIME RETURNS / PHYSICAL PAYOFF Time suddenly snaps back to normal speed. Gravity and existing momentum resume simultaneously. Every object continues FROM ITS EXISTING WORLD-SPACE POSITION. The protagonist completes her backward fall naturally. The sunglasses continue from their suspended position and land according to their existing momentum and gravity. The coffee cup continues from its own separate position, impacts the cobblestone ground, the partially detached lid reacts naturally, and remaining coffee spills irregularly through the real opening and impact point. The OPEN flip phone continues from its own separate position, hits the ground and makes ONE small physically believable bounce. Objects land at DIFFERENT plausible locations. They do NOT suddenly converge beside the protagonist. CAMERA rapidly tilts/drops toward ground level to follow the final impacts. Finish with a cinematic low-angle composition showing the fallen protagonist and the scattered objects within the same believable sunset environment. Hard cut. BULLET-TIME CAMERA RULE — NON-NEGOTIABLE BULLET TIME = ALMOST-FROZEN PHYSICAL WORLD + FREELY MOVING CAMERA. Objects stay in WORLD SPACE. Camera moves through WORLD SPACE. Close-up is created ONLY by reducing camera-to-object distance. Never: move objects toward the lens, artificially enlarge objects, teleport objects, regenerate macro versions. STRICT CAMERA ROUTE: FULL FROZEN TABLEAU → CAMERA DOLLIES TO SUNGLASSES → HOLD → 20–30° CAMERA ORBIT → CAMERA TRAVELS TO COFFEE → HOLD → SMALL CAMERA PARALLAX → CAMERA TRAVELS TO PHONE → ESTABLISH COMPLETE PHONE → MOVE TO DISPLAY → HOLD → CAMERA DOLLIES BACK TO COMPLETE TABLEAU → TIME RETURNS CONTINUITY / CAUSALITY Wide shot → medium shot → macro shot = SAME physical object viewed from different camera distances. Sunglasses: same object, same design, same trajectory, same world-space identity. Coffee: same cup, same lid, same coffee, same rotation, same world-space identity. Phone: same open clamshell phone, same housing, hinge, keypad, display, open angle and world-space identity. Every visible change must have a physical cause. Collision causes recoil. Collision momentum separates sunglasses. Finger release changes phone position. Hand release + collision momentum rotates cup. Cup rotation/liquid inertia partially opens lid. Coffee escapes only through the physical gap. Camera movement creates apparent object scale. Gravity resumes final fall. Treat the entire sequence as ONE continuous practical-effects event photographed with a motion-control cinema camera. IDENTITY / PROP LOCK ONE protagonist. ONE secondary person. ONE Labrador. ONE leash. ONE pair of sunglasses. ONE coffee cup. ONE lid. ONE OPEN flip phone. Before collision: RIGHT HAND = phone. LEFT HAND = coffee. Sunglasses = worn. After collision: RIGHT HAND = EMPTY. LEFT HAND = EMPTY. Sunglasses = separated. No second phone. No second cup. No second sunglasses. No additional dog. No additional person. No unexplained props. No duplication. No teleportation. No unexplained scale changes. VISUAL PRIORITY 1. exact protagonist identity from REFERENCE IMAGE 1 2. natural eyes and facial anatomy 3. stable hairstyle and body proportions 4. exact clothing and accessories 5. exact sunglasses from REFERENCE IMAGE 3 6. stable phone geometry 7. empty hands after release 8. continuous physical trajectories 9. realistic environment inspired by REFERENCE IMAGE 2 PHOTOGRAPHIC REALISM Ultra-photorealistic LIVE-ACTION. High-budget international luxury fashion campaign. Real human anatomy. Natural skin pores. Natural facial micro-expressions. Detailed realistic hair. Real manufactured sunglasses. Real paper cup. Real plastic lid. Real liquid coffee. Real early-2000s flip phone. Real object mass, inertia, gravity, momentum and surface tension. ARRI Alexa 35 cinematic character. Premium cinema optics. Motivated sunset lighting inspired by REFERENCE IMAGE 2. Controlled highlights. Natural skin tones. Realistic optical depth of field. Shallow macro depth of field during object inspections. Subtle 35mm film texture. Restrained luxury editorial colour grade. Natural colours. Sharp optical clarity. Cinematic photographic texture. Bullet-time must feel like REAL high-speed practical photography with a motion-control cinema camera, NOT CGI product animation. 4K / Ultra HD. Maximum facial detail. Maximum hair detail. Maximum material fidelity. Stable identity. Stable geometry. Stable prop continuity.

Made with seedance 2.5 Prompt: Create ONE continuous 12-second, 9:16, ultra-photorealistic LIVE-ACTION luxury fashion film. IMPORTANT REFERENCE MAPPING: REFERENCE Image = PRIMARY CHARACTER. Use the FIRST uploaded reference image of the woman. REFERENCE image2 = ENVIRONMENT. Use the SECOND uploaded reference image of the square. REFERENCE David Carbon = HERO OBJECT. Use the THIRD uploaded reference image of the sunglasses. Do NOT refer to these images as Image, image2 or David Carbon. Use the reference images according to their upload order. CHARACTER — REFERENCE IMAGE 1 Preserve the exact woman from REFERENCE IMAGE 1 throughout the entire video: same facial identity, facial structure, natural eyes, hairstyle, body proportions, skin appearance, clothing, footwear, jewelry, accessories and overall appearance. Do not copy the original background from REFERENCE IMAGE 1. The protagonist is the ONLY main character. ENVIRONMENT — REFERENCE IMAGE 2 Use REFERENCE IMAGE 2 only for visual language: architecture, atmosphere, warm sunset lighting, materials, monumental scale and cobblestone character. Create a NEW believable cinematic pedestrian space inspired by it. Do NOT reproduce its exact composition, exact camera angle or exact street layout. Provide enough open pedestrian space for natural walking and the collision. Respect real-world spatial logic: pedestrians remain in pedestrian areas, architecture has realistic scale and perspective, no impossible geometry. HERO OBJECT — REFERENCE IMAGE 3 The sunglasses shown in REFERENCE IMAGE 3 are the ONE and ONLY HERO OBJECT. Preserve their recognizable: shape, proportions, oversized shield silhouette, dark continuous lens, thin metallic/gold frame, temples, hinge construction, surface details, colour and material. The SAME physical sunglasses must remain recognizable: when worn by the protagonist, when released, during bullet-time macro inspection, and after landing. Do not redesign, replace, duplicate or regenerate the sunglasses. EXACT OBJECT COUNT Exactly: ONE protagonist. ONE secondary passing person. ONE Labrador. ONE leash. ONE pair of sunglasses from REFERENCE IMAGE 3. ONE takeaway paper coffee cup. ONE plastic drinking lid. ONE silver-grey OPEN clamshell flip phone. No duplicate objects or people. PERSISTENT PHONE There is exactly ONE phone in the entire video. It is a compact early-2000s silver-grey OPEN clamshell flip phone. Upper half: small illuminated display and speaker. Lower half: physical numeric keypad, navigation buttons and microphone. Visible central mechanical hinge. LOCK its appearance throughout: same silver-grey colour, same dimensions, same thickness, same hinge, same display, same keypad, same buttons, same open angle. The same phone is seen in wide, medium and macro shots. It never transforms into another phone. PERSISTENT COFFEE Exactly ONE medium disposable PAPER coffee cup with ONE lightweight plastic drinking lid and dark coffee inside. Same cup, same lid, same coffee and same proportions throughout. Before collision the lid is properly attached. Coffee remains inside until a real physical opening appears. HAND OWNERSHIP Before collision: RIGHT HAND = ONE OPEN flip phone held to the RIGHT ear. LEFT HAND = ONE coffee cup. Sunglasses = naturally worn by the protagonist. After collision: RIGHT HAND = COMPLETELY EMPTY. LEFT HAND = COMPLETELY EMPTY. Nothing replaces the phone or cup. Nothing remains attached to either palm. 0.0–2.0s — CINEMATIC CHARACTER REVEAL Begin with an extreme low close-up of the protagonist’s black leather heeled boots walking naturally across the pedestrian space. Camera performs ONE elegant continuous movement: smooth crane upward + gentle backward tracking. Reveal progressively: boots → legs → ripped light-blue baggy jeans → black corset → white tank top → jewelry/accessories → sunglasses → face → nearly full body. The protagonist wears the SAME sunglasses from REFERENCE IMAGE 3. She holds the SAME OPEN silver-grey flip phone to her RIGHT ear and the SAME coffee cup in her LEFT hand. She is actively having a phone conversation. Show subtle realistic speech: natural lip movement, jaw movement and mouth articulation. Maintain exact identity from REFERENCE IMAGE 1. Premium live-action fashion cinematography. 2.0–3.7s — WALKING / SECONDARY PERSON Maintain smooth frontal tracking. The protagonist continues walking naturally through the pedestrian area. Exactly ONE secondary person approaches from the opposite direction. That person holds exactly ONE leash attached to exactly ONE Labrador. The Labrador walks slightly ahead and gently pulls the person forward. They remain background/supporting elements. Maintain: stable protagonist identity, stable hairstyle, stable clothing, stable sunglasses, same phone, same coffee. 3.7–4.4s — ACCIDENTAL COLLISION As they pass each other, the secondary person’s ELBOW accidentally clips the protagonist’s arm/upper torso. Small, accidental, believable contact. The protagonist naturally recoils backward. This SAME collision causes THREE physical release events. SUNGLASSES The sunglasses from REFERENCE IMAGE 3 receive ONE short realistic outward impulse. They separate naturally from the protagonist’s face. They travel only a short physically believable distance. They do NOT fly toward the camera. COFFEE The SAME coffee cup leaves the LEFT hand. It receives one short outward/downward rotational impulse. The cup tilts and rotates. Because of the rotation and liquid inertia, ONE EDGE of the lightweight plastic lid partially pops loose from the cup rim. The lid does not disappear and does not explode away. A real physical gap forms between lid and rim. ONLY THEN does dark coffee begin escaping through this opening. Initial liquid movement is restrained. PHONE The SAME OPEN clamshell phone leaves the RIGHT hand. It receives one short outward/upward impulse. It keeps the SAME open angle and physical design. The instant it separates from the fingers: RIGHT HAND = EMPTY. The instant the cup separates: LEFT HAND = EMPTY. FACE / HAIR CONTINUITY Preserve the exact face from REFERENCE IMAGE 1 during the entire collision. The natural human eyes already exist behind the sunglasses. When the sunglasses separate, reveal the SAME normal eyes: stable pupils, eyelids, gaze direction, brows, nose, cheekbones and facial symmetry. Do not regenerate or alter the face. Hair remains stable with only subtle realistic inertia. No sudden hairstyle change. 4.4–5.2s — BULLET-TIME ESTABLISHMENT Time decelerates dramatically to approximately 2–3% normal speed. DO NOT immediately go into macro. FIRST show a clear medium-wide frozen view of the entire accident. The protagonist is beginning to fall backward. BOTH HANDS ARE EMPTY. Establish fixed WORLD-SPACE anchors: • sunglasses suspended near their release position; • coffee cup suspended lower and toward the LEFT-hand release side; • partially detached lid still connected to or immediately beside the cup; • restrained coffee beginning to escape through the opening; • OPEN flip phone suspended toward the RIGHT-hand release side. Objects move only microscopically. They do NOT move toward the camera. The CAMERA is the main moving element. 5.2–6.8s — SUNGLASSES HERO INSPECTION The sunglasses remain almost completely stationary at their existing world-space position. CAMERA physically dollies toward them. The sunglasses become larger ONLY because the camera gets closer. Once close, slow the camera dramatically. HOLD. Perform a restrained 20–30 degree camera orbit/parallax around the almost-stationary sunglasses. Reveal: dark shield lens, thin metallic/gold frame, temples, hinges, edges, material thickness, surface reflections, tiny manufacturing details. Use shallow photographic macro depth of field. The protagonist and sunset environment remain softly recognizable in the background. The sunglasses must look like a real luxury fashion accessory photographed with a macro cinema lens, NOT CGI product animation. Complete the inspection before moving away. 6.8–8.3s — COFFEE / LIQUID INSPECTION Only after completing the sunglasses inspection, the CAMERA leaves them at their existing world-space position. Travel diagonally through the frozen scene toward the SAME coffee cup. THE CUP DOES NOT MOVE TOWARD THE CAMERA. Hold a photographic macro close-up. Show: same paper cup, same lightweight plastic lid, ONE partially detached lid edge, clear physical gap, dark coffee escaping ONLY through that gap. Real restrained liquid physics: thin irregular stream, imperfect liquid sheet, several differently sized droplets, realistic surface tension, natural reflections. No explosive splash. No decorative CGI liquid. No perfect artificial shapes. Coffee advances only microscopically during bullet time. Perform a small restrained lateral/parallax camera movement around the cup, lid and droplets. HOLD long enough to see paper texture, plastic texture, liquid thickness and individual droplets. 8.3–9.8s — FLIP PHONE INSPECTION Only after coffee inspection, the CAMERA travels away from the cup. The cup, lid and droplets remain at their existing world-space positions. CAMERA moves through the same frozen scene toward the SINGLE OPEN silver-grey clamshell phone. THE PHONE DOES NOT MOVE TOWARD THE CAMERA. First establish the complete phone silhouette: same silver-grey housing, same upper display, same lower keypad, same central hinge, same open angle. Then CAMERA physically approaches the existing upper display. Extreme photographic macro close-up. The illuminated display reads: BOSS with one small realistic phone number underneath. HOLD. Show: real housing material, hinge, keypad texture, small scratches, surface wear, screen reflections. The phone does NOT transform to reveal its screen. It is the SAME phone seen from the beginning. The protagonist’s RIGHT HAND remains completely EMPTY in the background. 9.8–10.4s — COMPLETE FROZEN TABLEAU After phone inspection, CAMERA performs a fast but perfectly smooth dolly backward. All objects remain at their existing world-space positions. Reveal: same protagonist falling backward, both hands empty, same sunglasses, same coffee cup, same partially detached lid, same suspended coffee droplets, same OPEN flip phone, exactly one secondary person, exactly one Labrador. All positions must remain spatially consistent with the original collision and release trajectories. No object follows the camera. No object teleports. No object regenerates. Brief HOLD on the complete frozen tableau. 10.4–12.0s — TIME RETURNS / PHYSICAL PAYOFF Time suddenly snaps back to normal speed. Gravity and existing momentum resume simultaneously. Every object continues FROM ITS EXISTING WORLD-SPACE POSITION. The protagonist completes her backward fall naturally. The sunglasses continue from their suspended position and land according to their existing momentum and gravity. The coffee cup continues from its own separate position, impacts the cobblestone ground, the partially detached lid reacts naturally, and remaining coffee spills irregularly through the real opening and impact point. The OPEN flip phone continues from its own separate position, hits the ground and makes ONE small physically believable bounce. Objects land at DIFFERENT plausible locations. They do NOT suddenly converge beside the protagonist. CAMERA rapidly tilts/drops toward ground level to follow the final impacts. Finish with a cinematic low-angle composition showing the fallen protagonist and the scattered objects within the same believable sunset environment. Hard cut. BULLET-TIME CAMERA RULE — NON-NEGOTIABLE BULLET TIME = ALMOST-FROZEN PHYSICAL WORLD + FREELY MOVING CAMERA. Objects stay in WORLD SPACE. Camera moves through WORLD SPACE. Close-up is created ONLY by reducing camera-to-object distance. Never: move objects toward the lens, artificially enlarge objects, teleport objects, regenerate macro versions. STRICT CAMERA ROUTE: FULL FROZEN TABLEAU → CAMERA DOLLIES TO SUNGLASSES → HOLD → 20–30° CAMERA ORBIT → CAMERA TRAVELS TO COFFEE → HOLD → SMALL CAMERA PARALLAX → CAMERA TRAVELS TO PHONE → ESTABLISH COMPLETE PHONE → MOVE TO DISPLAY → HOLD → CAMERA DOLLIES BACK TO COMPLETE TABLEAU → TIME RETURNS CONTINUITY / CAUSALITY Wide shot → medium shot → macro shot = SAME physical object viewed from different camera distances. Sunglasses: same object, same design, same trajectory, same world-space identity. Coffee: same cup, same lid, same coffee, same rotation, same world-space identity. Phone: same open clamshell phone, same housing, hinge, keypad, display, open angle and world-space identity. Every visible change must have a physical cause. Collision causes recoil. Collision momentum separates sunglasses. Finger release changes phone position. Hand release + collision momentum rotates cup. Cup rotation/liquid inertia partially opens lid. Coffee escapes only through the physical gap. Camera movement creates apparent object scale. Gravity resumes final fall. Treat the entire sequence as ONE continuous practical-effects event photographed with a motion-control cinema camera. IDENTITY / PROP LOCK ONE protagonist. ONE secondary person. ONE Labrador. ONE leash. ONE pair of sunglasses. ONE coffee cup. ONE lid. ONE OPEN flip phone. Before collision: RIGHT HAND = phone. LEFT HAND = coffee. Sunglasses = worn. After collision: RIGHT HAND = EMPTY. LEFT HAND = EMPTY. Sunglasses = separated. No second phone. No second cup. No second sunglasses. No additional dog. No additional person. No unexplained props. No duplication. No teleportation. No unexplained scale changes. VISUAL PRIORITY 1. exact protagonist identity from REFERENCE IMAGE 1 2. natural eyes and facial anatomy 3. stable hairstyle and body proportions 4. exact clothing and accessories 5. exact sunglasses from REFERENCE IMAGE 3 6. stable phone geometry 7. empty hands after release 8. continuous physical trajectories 9. realistic environment inspired by REFERENCE IMAGE 2 PHOTOGRAPHIC REALISM Ultra-photorealistic LIVE-ACTION. High-budget international luxury fashion campaign. Real human anatomy. Natural skin pores. Natural facial micro-expressions. Detailed realistic hair. Real manufactured sunglasses. Real paper cup. Real plastic lid. Real liquid coffee. Real early-2000s flip phone. Real object mass, inertia, gravity, momentum and surface tension. ARRI Alexa 35 cinematic character. Premium cinema optics. Motivated sunset lighting inspired by REFERENCE IMAGE 2. Controlled highlights. Natural skin tones. Realistic optical depth of field. Shallow macro depth of field during object inspections. Subtle 35mm film texture. Restrained luxury editorial colour grade. Natural colours. Sharp optical clarity. Cinematic photographic texture. Bullet-time must feel like REAL high-speed practical photography with a motion-control cinema camera, NOT CGI product animation. 4K / Ultra HD. Maximum facial detail. Maximum hair detail. Maximum material fidelity. Stable identity. Stable geometry. Stable prop continuity.

Oogie

18,923 Aufrufe • vor 23 Tagen

Bedroom chaos turns into midnight confidence with a seamless transition that hits right on the beat. Seedance 2.5 on DomoAI official Prompt FORMAT 10 seconds, 2 shots. Shot 1: Indoor bedroom, 0.0–5.0s. Shot 2: Outdoor night street, 5.0–10.0s. Transition: seamless hard cut exactly on shoe impact. Style: photorealistic live-action, premium cinematic commercial, realistic movement/physics, authentic handheld cinematography. SHOT 1 — INDOOR BEDROOM | 0.0–5.0s ENVIRONMENT Minimalist young woman's @[Image 1](image_1) private bedroom in daylight; clean, modern, intimate, naturally lived-in. Large curtain several meters behind Sharon, simple desk/console farther behind, minimal personal objects and subtle decoration. Enough depth for subject separation. Background softly out of focus; Sharon remains sharp and readable. CAMERA / LIGHTING Eye-level handheld, medium-wide/full-body framing with room for lateral movement and shoe actions, moderate shallow depth of field. Soft natural daylight, natural skin tones, soft highlights, gentle realistic shadows, warm clean atmosphere. Camera is operated physically with Sharon: lateral tracking, short push-in, reactive pull-back, quick pans, tilts and reframing. Never perfectly smooth or automated; movement is quick, light, imperfect and physically motivated by her actions. ACTION + CAMERA 0.0–1.1s — Sharon enters from RIGHT holding TWO SHOES, one in each hand, and walks toward center. Camera: handheld lateral tracking LEFT, physically stepping sideways while keeping medium-wide framing. 1.1–1.8s — Sharon @[Image 1](image_1) stops near center, raises one shoe toward camera as if showing it, then brings it toward her nose. Camera: short handheld push-in; keep face and shoe sharp. 1.8–2.4s — Sharon smells the shoe, immediately recoils with surprised disgust, pulls her face away and gives a short head shake. Camera: small reactive pull-back, then immediately settle toward her face. 2.4–3.0s — Sharon casually throws the first shoe toward the side of the room. Camera: quick reactive pan following the shoe briefly, then fast pan back to Sinta; believable handheld imperfection. 3.0–3.8s — Sharon shifts sideways, focuses on the second shoe, and throws it vertically upward. Camera: tilt up following the shoe; as it reaches the top of its trajectory, quickly tilt back down toward Sinta while keeping awareness of her and the descending shoe. 3.8–4.4s — Sharon tracks the descending shoe with her eyes, adjusts footing, rotates slightly sideways and prepares a high side kick. Camera: short lateral handheld adjustment keeping body and falling shoe in frame; subtle natural Dutch tilt may develop. 4.4–5.0s — Shoe descends into kicking range. Sharon performs a fast, precise HIGH SIDE KICK: leg extends sharply sideways, torso rotates slightly, supporting leg grounded, arms naturally counterbalance, eyes locked on the shoe. Full real-time. Camera: quick handheld lateral reposition and reactive pan following the kick; frame momentarily shifts with the force. EXACT MATCH CUT — 5.0s Hard cut at the exact moment Sharons extended foot contacts the airborne shoe. The kick is still at full speed and the cut happens DURING the action. Outdoor shot continues the same body direction, leg extension, torso rotation and momentum. SHOT 2 — NIGHT / QUIET CITY STREET | 5.0–10.0s ENVIRONMENT Relatively quiet modern urban street at night with broad paved roadway, streetlights, scattered storefronts, illuminated windows, trees, signage and distant buildings creating layered practical lighting. Sparse distant traffic. Spacious, cinematic, quiet. A WHITE SPORT MOTORCYCLE is behind Sinta and slightly toward one SIDE of frame, not centered directly behind her. Open street creates a clear diagonal path from Sharon to the motorcycle. LIGHTING / OUTFIT Naturalistic night lighting: warm streetlights mixed with cooler ambient city illumination, realistic highlights on black riding outfit, natural reflections on white motorcycle and asphalt, cinematic contrast with realistic exposure. Sharon wears a coordinated black-and-white motorcycle riding set: fitted black racing jacket with clean white shoulder/sleeve panels; fitted black short riding pants with subtle white detailing; compact black knee/shin protection; black motorcycle gloves with small white accents; clean white low-top sport sneakers; white crew socks to mid-calf; loose natural hair; no helmet. Motorcycle: white sport motorcycle. CAMERA Handheld kinetic cinematography. Operator physically follows Sharon using diagonal tracking, short arc movement, reactive panning, slight push-in and quick reframing. Never a perfectly programmed path; camera reacts to her changing body direction. ACTION + CAMERA 5.0–5.5s — HARD CUT. Sharon appears outdoors continuing the indoor side kick: kicking leg extended, torso rotated, momentum continuing. White sport motorcycle partially visible behind her toward one side. Camera immediately reacts. Camera: quick handheld pan/reframe catching the continuing kick trajectory. 5.5–6.3s — Sharon lowers her kicking leg naturally and does not stop. She moves DIAGONALLY across frame toward the motorcycle, forward-diagonal rather than straight backward/sideways, gradually turning torso and hips toward it while moving. Camera: handheld diagonal tracking with slight forward tracking plus lateral shift; keep Sharon dominant while motorcycle remains visible near the side. 6.3–7.2s — Sharon continues diagonally; body progressively rotates toward motorcycle. This is a traveling diagonal turn, NOT a stationary turn-in-place. Feet keep carrying her forward while torso rotates. Camera: short handheld arc around Sharon while continuing diagonal tracking; slight angle change and subtle pan to keep her centered; motorcycle remains partially visible at the side. 7.2–8.0s — SLOW MOTION BEGINS. Sharon is already mid-diagonal movement toward motorcycle. Body continues diagonal rotation; loose hair swings naturally; jacket moves with rotation; movement becomes elegant and cinematic. Camera: slightly smoother handheld character, subtle handheld push-in combined with short arc; stay physically close; motorcycle remains visible toward the side. 8.0–8.4s — Gradually return to normal speed. Sharon completes diagonal rotation and now faces motorcycle more directly. Camera: normal handheld movement; quick reframing keeps Sharon and motorcycle visually connected. 8.4–10.0s — Sharon moves confidently toward the white sport motorcycle, purposeful and energetic. Motorcycle stays slightly off-center. Camera: handheld forward tracking, maintaining medium-wide framing, subtle push-in, then small reactive pan toward motorcycle as Sharon reaches it. End with Sharon immediately beside the motorcycle. SPEED PRIORITY 0.0–5.0s: full real-time; shoe throw and high side kick are fast; match cut at full-speed impact. 5.0–7.2s: full real-time immediately after cut. 7.2–8.0s: subtle slow motion only during diagonal body rotation toward motorcycle. 8.0–10.0s: normal real-time. MATCH CUT PRIORITY Cut exactly on impact. Preserve across the cut: leg extension, torso rotation, body orientation, movement direction, screen position and continuous physical momentum. Location, time of day, lighting, wardrobe and motorcycle may change entirely through the hard cut. The transition must feel instantaneous, physical, stylish and seamless. #DomoAI #DomoAICPP

Bedroom chaos turns into midnight confidence with a seamless transition that hits right on the beat. Seedance 2.5 on DomoAI official Prompt FORMAT 10 seconds, 2 shots. Shot 1: Indoor bedroom, 0.0–5.0s. Shot 2: Outdoor night street, 5.0–10.0s. Transition: seamless hard cut exactly on shoe impact. Style: photorealistic live-action, premium cinematic commercial, realistic movement/physics, authentic handheld cinematography. SHOT 1 — INDOOR BEDROOM | 0.0–5.0s ENVIRONMENT Minimalist young woman's @[Image 1](image_1) private bedroom in daylight; clean, modern, intimate, naturally lived-in. Large curtain several meters behind Sharon, simple desk/console farther behind, minimal personal objects and subtle decoration. Enough depth for subject separation. Background softly out of focus; Sharon remains sharp and readable. CAMERA / LIGHTING Eye-level handheld, medium-wide/full-body framing with room for lateral movement and shoe actions, moderate shallow depth of field. Soft natural daylight, natural skin tones, soft highlights, gentle realistic shadows, warm clean atmosphere. Camera is operated physically with Sharon: lateral tracking, short push-in, reactive pull-back, quick pans, tilts and reframing. Never perfectly smooth or automated; movement is quick, light, imperfect and physically motivated by her actions. ACTION + CAMERA 0.0–1.1s — Sharon enters from RIGHT holding TWO SHOES, one in each hand, and walks toward center. Camera: handheld lateral tracking LEFT, physically stepping sideways while keeping medium-wide framing. 1.1–1.8s — Sharon @[Image 1](image_1) stops near center, raises one shoe toward camera as if showing it, then brings it toward her nose. Camera: short handheld push-in; keep face and shoe sharp. 1.8–2.4s — Sharon smells the shoe, immediately recoils with surprised disgust, pulls her face away and gives a short head shake. Camera: small reactive pull-back, then immediately settle toward her face. 2.4–3.0s — Sharon casually throws the first shoe toward the side of the room. Camera: quick reactive pan following the shoe briefly, then fast pan back to Sinta; believable handheld imperfection. 3.0–3.8s — Sharon shifts sideways, focuses on the second shoe, and throws it vertically upward. Camera: tilt up following the shoe; as it reaches the top of its trajectory, quickly tilt back down toward Sinta while keeping awareness of her and the descending shoe. 3.8–4.4s — Sharon tracks the descending shoe with her eyes, adjusts footing, rotates slightly sideways and prepares a high side kick. Camera: short lateral handheld adjustment keeping body and falling shoe in frame; subtle natural Dutch tilt may develop. 4.4–5.0s — Shoe descends into kicking range. Sharon performs a fast, precise HIGH SIDE KICK: leg extends sharply sideways, torso rotates slightly, supporting leg grounded, arms naturally counterbalance, eyes locked on the shoe. Full real-time. Camera: quick handheld lateral reposition and reactive pan following the kick; frame momentarily shifts with the force. EXACT MATCH CUT — 5.0s Hard cut at the exact moment Sharons extended foot contacts the airborne shoe. The kick is still at full speed and the cut happens DURING the action. Outdoor shot continues the same body direction, leg extension, torso rotation and momentum. SHOT 2 — NIGHT / QUIET CITY STREET | 5.0–10.0s ENVIRONMENT Relatively quiet modern urban street at night with broad paved roadway, streetlights, scattered storefronts, illuminated windows, trees, signage and distant buildings creating layered practical lighting. Sparse distant traffic. Spacious, cinematic, quiet. A WHITE SPORT MOTORCYCLE is behind Sinta and slightly toward one SIDE of frame, not centered directly behind her. Open street creates a clear diagonal path from Sharon to the motorcycle. LIGHTING / OUTFIT Naturalistic night lighting: warm streetlights mixed with cooler ambient city illumination, realistic highlights on black riding outfit, natural reflections on white motorcycle and asphalt, cinematic contrast with realistic exposure. Sharon wears a coordinated black-and-white motorcycle riding set: fitted black racing jacket with clean white shoulder/sleeve panels; fitted black short riding pants with subtle white detailing; compact black knee/shin protection; black motorcycle gloves with small white accents; clean white low-top sport sneakers; white crew socks to mid-calf; loose natural hair; no helmet. Motorcycle: white sport motorcycle. CAMERA Handheld kinetic cinematography. Operator physically follows Sharon using diagonal tracking, short arc movement, reactive panning, slight push-in and quick reframing. Never a perfectly programmed path; camera reacts to her changing body direction. ACTION + CAMERA 5.0–5.5s — HARD CUT. Sharon appears outdoors continuing the indoor side kick: kicking leg extended, torso rotated, momentum continuing. White sport motorcycle partially visible behind her toward one side. Camera immediately reacts. Camera: quick handheld pan/reframe catching the continuing kick trajectory. 5.5–6.3s — Sharon lowers her kicking leg naturally and does not stop. She moves DIAGONALLY across frame toward the motorcycle, forward-diagonal rather than straight backward/sideways, gradually turning torso and hips toward it while moving. Camera: handheld diagonal tracking with slight forward tracking plus lateral shift; keep Sharon dominant while motorcycle remains visible near the side. 6.3–7.2s — Sharon continues diagonally; body progressively rotates toward motorcycle. This is a traveling diagonal turn, NOT a stationary turn-in-place. Feet keep carrying her forward while torso rotates. Camera: short handheld arc around Sharon while continuing diagonal tracking; slight angle change and subtle pan to keep her centered; motorcycle remains partially visible at the side. 7.2–8.0s — SLOW MOTION BEGINS. Sharon is already mid-diagonal movement toward motorcycle. Body continues diagonal rotation; loose hair swings naturally; jacket moves with rotation; movement becomes elegant and cinematic. Camera: slightly smoother handheld character, subtle handheld push-in combined with short arc; stay physically close; motorcycle remains visible toward the side. 8.0–8.4s — Gradually return to normal speed. Sharon completes diagonal rotation and now faces motorcycle more directly. Camera: normal handheld movement; quick reframing keeps Sharon and motorcycle visually connected. 8.4–10.0s — Sharon moves confidently toward the white sport motorcycle, purposeful and energetic. Motorcycle stays slightly off-center. Camera: handheld forward tracking, maintaining medium-wide framing, subtle push-in, then small reactive pan toward motorcycle as Sharon reaches it. End with Sharon immediately beside the motorcycle. SPEED PRIORITY 0.0–5.0s: full real-time; shoe throw and high side kick are fast; match cut at full-speed impact. 5.0–7.2s: full real-time immediately after cut. 7.2–8.0s: subtle slow motion only during diagonal body rotation toward motorcycle. 8.0–10.0s: normal real-time. MATCH CUT PRIORITY Cut exactly on impact. Preserve across the cut: leg extension, torso rotation, body orientation, movement direction, screen position and continuous physical momentum. Location, time of day, lighting, wardrobe and motorcycle may change entirely through the hard cut. The transition must feel instantaneous, physical, stylish and seamless. #DomoAI #DomoAICPP

Sharon Riley

31,073 Aufrufe • vor 12 Tagen