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. Add configurable counting lines or regions to measure entries, exits, directional movement, and other real-world traffic metrics. #vehicles #MachineLearning #Highwayshow more

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 #MachineLearningshow more

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.show more

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:show more

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.show more

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 #AIshow more

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 returnsshow more

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.show more

🚀 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 tunedshow more

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.show more

⚡️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.show more

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:show more

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 Manipurshow more

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.show more

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.show more

You spend years training for the World Cup, then... lose to a cat. This Cat vs Human Football match rivalry was created using GPT Image 2 + Seedance 2.0 on RoboNeo #Roboneo Prompt Create a 15-second cinematic FIFA World Cup 2026 sports-comedy commercial. Every scene must happen strictly in the exact sequence listed below. Do NOT skip, merge, shorten, combine, or reorder any scene. Maintain perfect character consistency across all shots. MAIN CHARACTER: Athletic western blonde female soccer player, age 24, blue eyes, long blonde ponytail, red soccer jersey #8, red shorts, red socks, professional football boots. ANIMAL HERO: Sleek athletic grey cat with green eyes wearing a matching red soccer jersey. OPPONENTS: Two muscular female football players wearing white uniforms. ENVIRONMENT: FIFA World Cup 2026 atmosphere. Massive packed football stadium during golden hour. Warm sunlight, dramatic lens flares, vibrant green grass, roaring crowd, FIFA World Cup branding, international supporters waving USA, Canada, and Mexico flags. Premium global football-event energy. STYLE: Photorealistic live-action sports commercial, realistic human anatomy, Pixar-quality cat animation, Nike-style energy, dynamic camera movement, cinematic lighting, ultra-detailed textures, realistic football physics except for the cat's comedic athletic abilities. DURATION: 15 seconds total. SCENE 1 (0:00–0:02) — WORLD CUP OPENING High aerial establishing shot of a massive FIFA World Cup 2026 stadium at golden hour. Visible FIFA World Cup 2026 banners around the stadium. Crowd packed with supporters waving USA, Canada, and Mexico flags. A recognizable host-city landmark is visible in the distance. The blonde player in red jersey #8 dribbles confidently across the pitch while the grey cat runs beside her. Camera slowly pushes forward. Warm sunlight washes over the field. Massive crowd roar. On-screen title card appears briefly: "FIFA WORLD CUP 2026". SCENE 2 (0:02–0:03) — GAME ON Medium action shot. Two muscular opponents in white uniforms notice the cat and immediately shift their focus toward stopping it. The cat glances toward the ball with determination. Quick cinematic push-in. Crowd anticipation rises. SCENE 3 (0:03–0:05) — CAT SPEED BURST Ground-level tracking shot. The cat explodes forward between players' legs at impossible speed. Grass, dirt, and turf particles spray upward. Intense acceleration effect and realistic motion blur. Stadium crowd reacts with surprise. SCENE 4 (0:05–0:06) — PLAYER REACTION Extreme close-up of the blonde player. She smiles confidently, then her eyes suddenly widen in genuine surprise as she realizes how unbelievably fast the cat is moving. Lens flare sweeps across frame. SCENE 5 (0:06–0:08) — HERO CAT Low-angle hero close-up. The cat locks eyes on the ball. Golden sunlight creates a glowing halo around its silhouette. Slow-motion moment. Crowd noise softens briefly while heroic music rises. Fur detail and jersey fabric rendered with ultra-realistic quality. SCENE 6 (0:08–0:10) — FIRST DODGE Wide action shot. One defender launches a tackle. The cat instantly sidesteps and slips perfectly between both defenders. The tackle misses completely. The crowd erupts with laughter and excitement. SCENE 7 (0:10–0:12) — SLIDE CHAOS Both opponents commit to aggressive sliding tackles simultaneously. Massive dirt explosion. The cat effortlessly avoids both slides with perfect timing. The defenders collide with each other and tumble dramatically. Realistic physics, comedic timing. Crowd reaction intensifies. SCENE 8 (0:12–0:13) — DRIBBLE MASTER Dynamic tracking shot. The cat skillfully dribbles the ball through the chaos with incredible close control. Opponents tumble helplessly in the background. The blonde player watches in amused disbelief. Stadium energy reaches its peak. SCENE 9 (0:13–0:14) — IMPOSSIBLE SHOT Dramatic low-angle shot. The cat crouches beside the ball and looks upward. Tension builds. Suddenly the cat launches into an impossible move and strikes the ball toward goal. Cinematic speed ramp. Ball rockets through the air toward the net. SCENE 10 (0:14–0:15) — WORLD CUP GOAL & BRAND PAYOFF Ultra-cinematic goal shot. The football smashes into the back of the net at high speed. The net deforms naturally and ripples realistically with detailed cloth physics. Goal frame shakes subtly from impact. Crowd instantly explodes in celebration. Fans wave USA, Canada, and Mexico flags. The blonde player throws her hands up in disbelief and joy. The cat lands heroically and looks toward the roaring stadium. Freeze frame on the celebrating cat. On-screen tagline appears: "IMPOSSIBLE IS JUST KICKOFF." FIFA WORLD CUP 2026 logo appears prominently with premium commercial-grade branding. End on triumphant crowd roar and stadium atmosphere. CINEMATIC NOTES: Strict chronological sequence. No scene skipping, merging, or reordering. Fast-paced sports-commercial editing. Warm golden-hour color grading. Dynamic camera movement throughout. Premium FIFA World Cup 2026 advertising quality. Realistic football and net physics. Massive crowd reactions escalating throughout the film. Consistent character appearance across every shot. Photorealistic visuals with cinematic lens flares and broadcast-quality production values. Final goal must feel epic, emotional, and unmistakably FIFA World Cup 2026.show more

From sofa to stadium in a single leap. From... living room to world-class stadium in seconds. Argentina vs Brazil, one magical run, one unstoppable strike, and a celebration heard around the world. Create your World Cup moment with SeaArt, earn free Credits and win an iPhone 17. #SeaArtWorldCup Made with Seedance Credit: SeaArt.Ai🐋 SeaArt Creator Lab Prompt: First-person POV from a comfortable reclining armchair in a cozy modern living room. From the very first frame, a large television mounted on the wall directly ahead is already showing a live Argentina vs Brazil football match in full swing. Soft afternoon sunlight streams through the windows, creating a relaxed match-day atmosphere. The viewer's legs are stretched out comfortably while wearing casual shorts, enjoying the game from a resting position. Authentic British football commentary and crowd noise play naturally from the television. At 0:02, a young woman wearing an appealing lavender-purple casual shorts outfit and a stylish half-French braid hairstyle enters from the right side of frame. She is a neutral football fan, not supporting either team. Drawn into the excitement of the match, she glances at the television, smiles, then accelerates into a sprint across the living room. At 0:04, she runs directly toward the television. The camera remains first-person and perfectly stable. At 0:05, she leaps into the TV screen in one continuous motion. No cuts, no scene jumps, no transitions breaking continuity. As she reaches the screen, the living room seamlessly dissolves away and transforms into a massive international football stadium hosting Argentina vs Brazil. Television audio smoothly expands into a deafening live stadium atmosphere. The transformation happens organically around the camera while preserving one uninterrupted shot. At 0:06, she lands smoothly on the pitch, still wearing the exact same lavender outfit and half-French braid. A single football rolls naturally toward her. IMPORTANT: Only one football exists throughout the entire video. The football must maintain perfect object permanence. The same ball remains continuously visible and physically consistent from first touch to goal. No duplication, replacement, morphing, teleportation, flickering, frame-to-frame jumps, texture changes, scaling changes, disappearing ball, floating ball, or AI artefacts. Realistic football physics only. At 0:07, she controls the football with a clean first touch. At 0:08–0:11, she dribbles continuously between Argentina and Brazil players. Every touch follows realistic momentum, spacing, and foot-to-ball contact. Defenders react naturally. No clipping, collision errors, or unnatural movements. At 0:11, she approaches the edge of the penalty area. At 0:12, she unleashes a powerful strike using the same football. The camera clearly tracks the football's entire flight path from her foot to the goal in one uninterrupted motion. Realistic spin, realistic speed, realistic trajectory. At 0:13, the football smashes into the top corner of the net. The net deforms naturally and ripples realistically. The crowd explodes with excitement. Authentic British football commentator shouts: "What a strike! Absolutely sensational!" At 0:14, she turns and sprints toward the corner flag as the camera follows closely. For the final second, she leaps high into the air and performs the iconic Siuuu celebration, rotating and landing with feet apart and arms extended downward while facing the roaring crowd. Her half-French braid swings dramatically behind her. Stadium lights illuminate the scene as thousands of fans celebrate. One continuous unbroken shot, no cuts, no scene resets, seamless living-room-to-stadium transformation, cinematic football commercial quality, authentic British football commentary, realistic player movement, physically accurate football physics, strict ball continuity, stable camera motion, premium sports broadcast visuals, dramatic stadium atmosphere, crowd chants, sprinting footsteps, grass impact sounds, powerful strike, realistic net ripple, ultra-realistic visuals, 15-second duration, 16:9 horizontal format, no logos, no text overlays, no subtitles, no watermark, no flickering objects, no AI artefacts, no visual glitches.show more

john wick seedance text to video prompt： [STYLE /... CINEMATIC SETUP] A 10.5-second, 16:9 photorealistic AAA action-game cinematic rendered at real-time speed with no slow motion. The setting is a cramped, cluttered late-night Asian restaurant connected to a rain-soaked street. Cyan-green fluorescent light, red neon and warm practical lamps create a high-contrast mixed-light environment, with reflections across wet floors and pavement. Shoot with a 35mm spherical lens, shallow-to-moderate depth of field and cinematic motion blur appropriate to the actual speed of movement. Use close shoulder-mounted and handheld coverage, connecting seven short close-combat shots with fast hard cuts. The camera instinctively pans, retreats or drops with each block, takedown and collision while keeping the action and contact points readable. No dialogue, no subtitles and no BGM. Generate only synchronized rain, appliance hum, urgent footsteps, fabric movement, body impacts, gunshots, metal contact and breaking glass. [IMAGE REFERENCES] No external still-image reference. Follow the written character and environment descriptions consistently. If the platform supports reference video, use the supplied video only as a reference for editing rhythm, camera distance, action direction and lighting atmosphere, not for copying a specific actor’s identity. The protagonist remains the same lean, agile man in his early forties throughout the sequence: neck-length black hair swept back, a short beard, a tired but focused face, a slightly wrinkled black suit, white shirt and narrow black tie, all carrying faint rain and wear marks. Preserve his face, hairstyle, body proportions, clothing and screen direction across all seven shots. Keep every opponent visually distinct: a man in a blue work uniform, a bald man in a navy jacket, a heavy man in a black jacket, a bald counter attacker, a red-headband attacker, a red-jacketed armed attacker and a heavy man in a dark green coat outside. [TIMELINE SECOND BY SECOND] 0–1.9s: [Shoulder-height medium close-up, tight lateral handheld tracking, real-time speed] The protagonist stands on screen left, pinning the blue-uniformed attacker against a glass refrigerator with his left forearm and palm. He delivers two compact, weighted elbow and palm-heel strikes. Each impact drives the attacker’s head into the refrigerator door, loosening his white headband and leaving a small blood trace on the glass; the attacker finishes sliding down the door while the protagonist remains standing. 1.9–4.3s: [Medium shot transitioning into a high-angle overhead, shoulder-mounted drop, real-time speed] Hard cut near the restaurant’s rear entrance. The bald attacker in a navy jacket locks the protagonist from behind. The protagonist lowers his center of gravity, traps the attacker’s arm and rotates his hips, throwing him heavily over the shoulder onto the wet floor. The camera drops with them into an overhead view. Kneeling across the attacker’s torso, the protagonist draws a compact black pistol and fires one downward shot; recoil travels through his wrist and the attacker jolts once before becoming still. 4.3–5.9s: [Tight medium shot, lateral handheld follow, real-time speed] Hard cut with both men already upright. A heavy attacker in a black jacket swings from screen right. The protagonist slips outside the punch, allowing it to pass close to his face, circles behind the attacker and locks his shoulder and neck off balance. He presses the pistol close to the side of the attacker’s head and fires. The muzzle flash briefly illuminates both faces; the attacker’s head and shoulders snap backward and his body begins to collapse. 5.9–7.9s: [Counter-height medium close-up, subtle handheld push-in, real-time speed] Hard cut to the restaurant counter. Another bald attacker bends forward and clamps around the protagonist’s waist. The protagonist pins the attacker’s head and neck under his left arm while grabbing a short, rigid pointed utensil from the counter. He drives two compact downward thrusts into the upper shoulder and side of the neck. Each contact bends the attacker’s knees further; a restrained amount of blood marks the shirt and counter edge before the attacker hangs helplessly beneath the protagonist’s controlling arm. 7.9–9.0s: [Two-person medium close-up, fast pan with a short retreat, real-time speed] Hard cut as the red-headband attacker rushes into close range. He throws a wide hook from screen right. The protagonist raises his forearm to block, catches the wrist and pulls it outward, then drives a palm heel and forearm into the attacker’s face. The camera retreats with the impact as the attacker loses his balance and staggers toward the rear right of the frame. 9.0–9.9s: [Low-angle wide shot, slight arc around the action, real-time speed] Hard cut to a wider section of the restaurant. The red-jacketed armed attacker advances from screen left. Holding a long black firearm with both hands, the protagonist uses it as a blunt weapon and swings horizontally from right to left. The weapon strikes the attacker’s upper chest and shoulder, rotating his torso, crossing his feet and sending him off balance toward screen left. 9.9–10.5s: [Exterior rainy-street medium shot, fast parallel tracking, real-time speed] Hard cut outside the restaurant. The protagonist already controls a heavy attacker in a dark green coat and uses his forward momentum to drive the man’s head and upper body into the side window of a parked black station wagon. The glass bursts inward at the contact point, scattering both large and fine fragments. The attacker folds through the broken window while the protagonist regains stable footing beside the car, ending with glass fragments still falling. [STYLE & QUALITY BOOSTERS] Maintain the protagonist’s face, black suit, white shirt, tie, hairstyle and body proportions through every hard cut. The pistol, pointed utensil, injuries and blood marks must appear only in their designated shots and must never morph or change ownership. Throws, recoil, strike reactions, loss of balance and window breakage must show believable weight, inertia and precise contact. Apply motion blur only to rapidly moving arms, weapons, glass fragments and camera-relative backgrounds. No sudden face or costume changes; no extra fingers, fused limbs or inverted joints; no morphing weapons, utensils or vehicles; no foot sliding or rubber-like collision reactions; no blood, bullet damage or glass fragments appearing before physical contact.show more

Ever wanted to enter the TV during a match?... Made this video using Seedance 2.0 on Picsart Try here: prompt First-person POV from a comfortable reclining armchair in a cozy modern living room decorated with elegant baby-pink accents. Soft baby-pink cushions, a pastel pink knitted blanket, subtle blush décor, and warm neutral furniture create a stylish modern aesthetic. From the very first frame, a large wall-mounted television directly ahead is already broadcasting a live Argentina vs Spain football match in full swing. Soft golden afternoon sunlight pours through the windows, filling the room with a warm, inviting match-day atmosphere. The viewer's legs are stretched out comfortably while wearing casual shorts, enjoying the game from a relaxed position. Authentic British football commentary and realistic crowd ambience naturally play from the television. At 0:02, a beautiful young woman wearing a fashionable baby-pink casual shorts outfit with white sneakers enters from the right side of the frame. Her hair is styled in a neat half-French braid that moves naturally with every step. She is a neutral football fan, supporting neither team. She notices the intensity of the Argentina vs Spain match, smiles with excitement, then suddenly accelerates into a sprint across the living room. At 0:04, she runs directly toward the television. The camera remains perfectly stable in a first-person perspective without shaking or zooming. At 0:05, she leaps directly into the television screen in one continuous motion. No cuts, no edits, no transitions. As she reaches the display, the entire living room organically dissolves into a gigantic international football stadium hosting Argentina vs Spain. The television audio naturally expands into an overwhelming live stadium atmosphere while maintaining one uninterrupted continuous shot. At 0:06, she lands smoothly on the football pitch still wearing the exact same baby-pink outfit and identical half-French braid. A single football rolls naturally toward her. STRICT OBJECT PERMANENCE: Only one football exists during the entire video. The same football remains continuously visible from first touch until the goal. No duplication, replacement, teleportation, morphing, flickering, disappearing, texture changes, scaling inconsistencies, floating ball, clipping, frame jumps, or AI artefacts. Realistic football physics only. At 0:07, she cushions the ball perfectly with a controlled first touch. From 0:08–0:11, she dribbles continuously through both Argentina and Spain defenders using realistic footwork, believable acceleration, proper spacing, authentic body balance, and natural player reactions. Every touch follows realistic momentum with accurate football physics. No clipping, collision issues, or unnatural animation. At 0:11, she reaches the edge of the penalty area. At 0:12, she unleashes a powerful long-range strike using the same football. The camera smoothly tracks the ball's entire flight from her foot to the goal in one uninterrupted motion. Realistic spin, natural speed, believable trajectory, premium broadcast-quality tracking. At 0:13, the football rockets into the top corner of the net. The goal net stretches and ripples realistically as the stadium erupts. Authentic British football commentator shouts: "What a strike! Absolutely sensational!" Crowd chants become deafening. At 0:14, she turns and sprints toward the corner flag as the camera follows closely behind. For the final second, she leaps high into the air and performs the iconic Siuuu celebration, rotating before landing confidently with feet apart and arms extended downward while facing the roaring crowd. Her half-French braid swings dramatically through the air. Brilliant stadium floodlights illuminate the scene as tens of thousands of fans celebrate around her. **Ultra-realistic cinematic football commercial, premium sports broadcast quality, seamless living-room-to-stadium transformation, one continuous unbroken shot, authentic British football commentary, realistic player movement, physically accurate football physics, strict single-ball continuity, stable first-person camera, cinematic lighting, dramatic atmosphere, crowd chants, sprinting footsteps, grass impact sounds, realistic ball contact, powerful strike, natural net deformation, HDR, ultra-detailed textures, premium realism, 15-second duration, portrait 9:16, baby-pink aesthetic, no logos, no text overlays, no subtitles, no watermark, no flickering objects, no AI artefacts, no visual glitches.show more