Загрузка видео...

Не удалось загрузить видео

На главную

Casual photos in, simulation-ready 3D objects out! Introducing 🐊GATOR🐊, generative + agentic 3D object reconstruction. Here, humanoids interact with GATOR-reconstructed furniture [1/n] Website: Paper:

15,765 просмотров • 13 дней назад •via X (Twitter)

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Introducing Kaleido💮 from AI at Meta — a universal generative neural rendering engine for photorealistic, unified object and scene view synthesis. Kaleido is built on a simple but powerful design philosophy: 3D perception is a form of visual common sense. Following this idea, we formulate rendering purely as a sequence-to-sequence generation problem, successfully unifying neural rendering with the architecture principles behind modern language and video models. Unlike traditional neural rendering methods, Kaleido learns 3D purely in a data-driven way, without explicit 3D representations or structures. It acquires spatial understanding directly through large-scale video pretraining, then multi-view 3D data finetuning, inspired by how LLMs acquire textual common sense from large corpora before specialising in domains like coding. Through extensive ablations, we progressively modernised the architecture design and training strategies and tackled key scaling challenges in sequence-to-sequence generative rendering, arriving at a design that’s simple, versatile, and scalable. Kaleido significantly outperforms prior generative models in few-view settings, and remarkably is the first zero-shot generative method matches InstantNGP-level rendering quality in multi-view settings. We view Kaleido also as an alternative step towards world modeling that flexibly spans a spectrum of “realities": with many views, it faithfully reconstructs grounded reality; with fewer views, it imagines plausible unseen details. 🔗 Explore more results and paper:

Shikun Liu

22,507 просмотров • 1 год назад

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 просмотров • 9 месяцев назад

🚀 The Segment Anything Model (SAM) has been upgraded to SAM2, featuring an efficient image encoder for segmenting images and videos. But does SAM2 outperform SAM1 in medical image and video segmentation? We're thrilled to present our paper "Segment Anything in Medical Images and Videos: Benchmark and Deployment"! We comprehensively benchmark SAM2 across 11 medical image modalities and videos. 📄 Paper: 💻 Code: **Highlights:** 1. SAM2 doesn’t always outperform SAM1 in 2D medical images, but excels in video segmentation, making it more accurate and efficient for 3D images, such as CT and MR scans. 2. MedSAM still outperforms SAM2 on most 2D modalities, but SAM2 surpasses MedSAM for 3D image segmentation in a slice-by-slice approach. 3. Segmentation performance varies with model size; sometimes the smallest model outperforms larger ones. 4. Fine-tuning SAM2 significantly boosts its performance for medical image segmentation. While SAM2 may struggle with challenging objects that have unclear boundaries or low contrast, it excels in generating good initial segmentation masks for common medical images and videos. However, the official interface doesn’t support medical data formats and has limitations on video length. To address this, we've developed a 3D Slicer Plugin and Gradio API for efficient 3D medical image and video segmentation. We invite you to try them out and provide feedback! 🔧 Deployment: - 3D Slicer Plugin: - Gradio API: (Note: Due to GPU limitations, the online API is available for only 12 hours and may be slow. We highly recommend deploying the Gradio API with your own computing resources: A big shoutout to Jun Ma (JunMa) who recently joined our UHN AI hub (UHN AI Hub) as Machine Learning Lead, and kudos to all co-authors: Sumin Kim, Feifei Li, Mohammed Baharoon (Mohammed Baharoon), Reza Asakereh, and Hongwei Lyu! This is true teamwork! Looking forward to collaborating with the community to advance 3D medical image and video segmentation foundation models! University Health Network U of T Department of Computer Science Department of Laboratory Medicine & Pathobiology Temerty Centre for AI in Medicine (T-CAIREM) Vector Institute #MedTech #AIinHealthcare #DeepLearning #MedicalImaging #SAM2 #MedSAM #AIResearch

Bo Wang

178,772 просмотров • 2 лет назад

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.

Johnn

73,556 просмотров • 5 месяцев назад

50 NEW internet rabbit holes you can spend hours exploring👇 No repeats. Just websites worth getting lost in. 🌐 1. — Spin the globe and listen to radio stations around the world 2. — Watch Earth's winds, oceans, and atmosphere move 3. — Explore weather patterns across the planet 4. — See fishing activity across the world's oceans 5. — Explore volcanoes and their history 6. — Explore satellite imagery of Earth 7. — Explore a 3D virtual globe 8. — Explore climate science and visualizations 9. — Dive into the science of our oceans 10. — Explore the weirdness of the internet 11. — Test your geography skills with location guessing games 12. — Travel the world without leaving your chair 13. — Discover locations using three-word addresses 14. — Explore street-level imagery from around the world 15. — Browse crowdsourced street imagery 16. — Explore interactive maps and geographic stories 17. — Explore historical geography through maps 18. — Discover old maps from around the world 19. — Explore geographic coordinates and locations 20. — Discover places and details on a world map 21. — Explore planets, asteroids, and spacecraft in 3D 22. — Discover worlds beyond our solar system 23. — Explore solar activity and space weather 24. — Track satellites and celestial objects 25. — Explore the night sky and astronomy events 26. — Explore a virtual universe 27. — Dive into the planets and moons of our solar system 28. — Experiment with interactive science simulations 29. — Explore interactive science and math explainers 30. — Explore physics concepts through linked explanations 31. — Ask questions and explore computational knowledge 32. — Learn math and science through interactive problems 33. — Explore interactive explanations of complex ideas 34. — Discover interactive science and math experiments 35. — Explore the strangest corners of science 36. — Discover scientific papers and research 37. — Search open-access academic research 38. — Dive into millions of academic articles 39. — Explore scientific preprints 40. — Fall down the mathematics rabbit hole 41. — Explore fascinating historical objects and stories 42. — Discover rare books and historical collections 43. — Explore photos, maps, and archives 44. — Browse the Louvre's art collection 45. — Explore artifacts from human history 46. — Discover objects from museums across Scandinavia 47. — Explore the world's music database 48. — Discover movies and endless film rabbit holes 49. — Explore sounds for focus, relaxation, and sleep 50. — Click a button and discover a random website Save this. Your next internet rabbit hole is waiting. 🔖 Follow Justin Brave💡 for more useful websites, AI tools & tech resources.

Justin Brave💡

122,630 просмотров • 25 дней назад

[VAE] by Hand ✍️ A Variational Auto Encoder (VAE) learns the structure (mean and variance) of hidden features and generates new data from the learned structure. In contrast, GANs only learn to generate new data to fool a discriminator; they may not necessarily know the underlying structure of the data. The International Conference on Learning Representations (ICLR) this year announced its first ever "Test of Time Award" to recognizes the VAE paper, published 10 years ago. This exercise demonstrates how to calculate a VAE by hand. [1] Given: ↳ Three training examples X1, X2, X3 ↳ Copy training examples to the bottom ↳ The purpose is to train the network to reconstruct the training examples. ↳ Since each target is a training example itself, we use the Greek word "auto" which means "self." This crucial step is what makes an autoencoder "auto." [2] Encoder: Layer 1 + ReLU ↳ Multiply inputs with weights and biases ↳ Apply ReLU, crossing out negative values (-1 -> 0) [3] Encoder: Mean and Variance ↳ Multiply features with two sets of weights and biases ↳ 🟩 The first set predicts the means (𝜇) of latent distributions ↳ 🟪 The second set predicts the standard deviation (𝜎) of latent distributions [4] Reparameterization Trick: Random Offset ↳ Sample epsilon ε from the normal distribution with mean = 0 and variance = 1. ↳ The purpose is to randomly pick a offset away from the mean. ↳ Multiply the standard deviation values with epsilon values. ↳ The purpose is to scale the offset by the standard deviation. [5] Reparameterization Trick: Mean + Offset ↳ Add the sampled offset to predicted mean ↳ The result are new parameters or features 🟨 as inputs to the Decoder. [6] Decoder: Layer 1 + ReLU ↳ Multiply input features with weights and biases ↳ Apply ReLU, crossing out negative values. Here, -4 is crossed out. [7] Decoder: Layer 2 ↳ Multiply features with weights and biases ↳ The output is Decoder's attempt to reconstruct the input data X from reparameterized distributions described by 𝜇 and 𝜎. [8]-[10] KL Divergence Loss [8] Loss Gradient: Mean 𝜇 ↳ We want 𝜇 to approach 0. ↳ A lot of math called SGVB simplifies the calculation of loss gradients to simply 𝜇 [9,10] Loss Gradient: Stdev 𝜎 ↳ We want 𝜎 to approach 1. ↳ A lot of math simplifies the calculation to 𝜎 - (1/ 𝜎) [11] Reconstruction Loss ↳ We want the reconstructed data Y (dark 🟧) to be the same as the input data X. ↳ Some math involving Mean Square Error simplifies the calculation to Y - X.

Tom Yeh

48,529 просмотров • 2 лет назад

GM my friends!🌞 Are you ready to fight?!😏🔥 Megan Fox, Kat Dennings 💪🏻 👉🏻Subscribe for more content!😎 Nano Banana 2 viao Hailuo AI & Kling 3.0 via Higgsfield AI Prompt: Hyper-realistic photorealistic portrait of cosplay Megam fox as Chun-Li from Street Fighter, crouching pose with hands on the ground, looking slightly directly to the camera with a neutral expression, extremely detailed face, 8k resolution, photorealistic skin texture with visible pores, subtle skin imperfections, realistic sweat droplets, micro skin details, individual eyelashes, realistic brown eyes with detailed iris texture and catchlights, natural subsurface scattering, ultra-detailed black hair with individual strands and realistic highlights, white silk ribbons in hair.She wears the classic blue qipao dress with gold embroidery, white high heels stilettos, black spiked leather wristbands with metallic studs, highly detailed fabric textures, realistic cloth folds and wrinkles, reflective surfaces on the dress. Torn paper collage effect in the background with two close-up realistic eye photos (one left, one right) overlapping the main image.Shot on Sony A1 camera with Sony FE 85mm f/1.4 GM lens, f/2.0 aperture, 1/160s shutter speed, ISO 100, cinematic natural studio lighting, soft key light from top left, subtle rim lighting, dramatic yet clean white background, sharp focus on face and body, shallow depth of field, bokeh effect, ultra-detailed 32k, masterpiece, best quality, photorealism, national geographic level detail, 8k raw photo, hyperrealistic textures, microscopic skin detail, octane render, unreal engine 5 quality. "style_and_quality": { "style": "photorealistic, high-fashion glamour photography, cinematic", "detail_level": "ultra high detail on skin pores, fabric texture, hair strands, reflections", "rendering": "realistic fabric details, glossy materials, accurate light interaction", "avoid": "cartoon, anime, illustration, painting, 3D render look" } }

KeorUnreal

34,802 просмотров • 4 месяцев назад

The architecture of this new world model is one of the most interesting things I've seen lately: Let me first explain how most world models work: They predict and render one frame at a time. If you are navigating in one of these worlds, and you look left, the model draws whatever looks right in the moment. Every time you change your viewpoint, the model has to imagine what should be there again, so it's very common for these models to "forget" what's in the world. For example, if you put a toy on the table, look away, then look back, the toy might not be there anymore. Tripo AI is releasing its Project Eden model, which works very differently: The model builds the world first, and then renders it based on that map. That map holds the real state of the world: the geometry, every object, where things are, what's already happened. The picture you see on screen gets generated from the map. This architecture flips the whole thing. Now, you get the following: 1. The world stops forgetting. Leave, come back, and the toy is still on the table because it lives in the map, not in the last frame you saw. 2. You can edit the world, and those changes persist for anyone who enters later. 3. Multiple people and AI agents can coexist in the world and see it from different perspectives. This is early research, but it's looking really promising. They just raised nearly $200M across two rounds to build it out. Tripo will be at SIGGRAPH 2026 (July 19–23, Los Angeles Convention Center). If you work in 3D, embodied AI, simulation, or anything spatial, go connect with them there.

Santiago

30,244 просмотров • 4 месяцев назад

🚀 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

37,592 просмотров • 1 год назад

AI VIDEOS HAVE MASTERED CAGE STRAP TENSION, HIGH-FREQUENCY 3D GEOMETRY, AND DYNAMIC HAND TO TEMPLE DEPTH OCCLUSION Framed in an indoor handheld perspective against a high relief geometric tiled wall with marbled faceting, long straight copper red hair falling past the shoulders, one hand casually raised in a relaxed salute near the temple, and a fitted black mini dress featuring intricate criss cross chest strapping and a pleated flounce hem maintaining immaculate anatomical contouring under soft ambient lighting. Nothing about the multi strap elastic tension, hand to head spatial separation, or repeating background geometry feels synthetic. Until recently, rendering a complex lattice of tight straps over curved anatomy while an articulated hand gestures near the face against a high contrast geometric relief was an immediate breaking point for generative video models. When intricate crisscrossing straps stretch over the chest, diffusion engines historically suffer from catastrophic topological confusion. Thin black straps typically merge into one another, blur directly into the cleavage boundary, or randomly snap and drift into detached floating pixels during movement. Introducing a delicate metallic accessory, like a gold heart pendant resting right at the intersection of tensioned fabric, compounds the artifacting, usually causing the metal to melt into skin layers or flicker into noisy temporal glitter. Furthermore, raising an open hand near the forehead and temple has always been a nightmare for temporal consistency: fingertips frequently fuse into hair strands, fingernails smudge against the brow, and earlier pipelines would hallucinate extra digits or distort the wrist angle. To make matters worse, the background consists of a rigid, three dimensional grid of beveled square tiles with organic marbling; in previous video generation architectures, even a fraction of a second of motion would cause that architectural grid to warp like liquid latex, jittering and melting out of alignment. Now, multi scale spatio temporal transformers resolve volumetric depth, occlusion boundaries, and material physics with shocking precision. Look at the structural lattice of the chest straps: each individual band holds its linear tension and casts a microscopic contact shadow against the skin without clipping or blurring into the neckline. The gold heart pendant remains physically anchored at the sternum, catching subtle ambient highlights while maintaining consistent mass and balance. Her raised hand near the temple demonstrates flawless spatial awareness, the fingers remain anatomically defined, the palm holds its perspective angle, and individual strands of vibrant red hair separate cleanly without fusing into the hand or the wall behind her. Even the lower ruffled hem of the dress preserves its flared architectural folds against the body without drifting. Most remarkably, the complex 3D beveled wall panels maintain rigid structural permanence throughout the shot; there is zero perspective warping, no line swimming, and no loss of the subtle marbled textures across the tiles. The real breakthrough in video generation isn't sweeping cinematic space battles or hyper stylized fantasy worlds; it’s mastering the unforgiving, microscopic physics of tensioned fabric straps, fine jewelry, and rigid geometric interior backdrops in a casual smartphone style video. The uncanny valley hasn't just narrowed, it has officially collapsed into reality.

aitifa uncut

18,984 просмотров • 7 дней назад

this model is so f*cking good for animations less hallucinations than gemini and it takes like 20 seconds to generate full clip + 1 min video costs only like ~$7 prompt that i used: Create a 15-second cinematic 3D animated product advertisement for supportive shoe insoles. Use a polished, high-end stylized 3D animation aesthetic with expressive but natural characters, soft cinematic lighting, realistic materials, believable anatomy, and subtle facial expressions. The scene takes place in a modern apartment hallway in the early morning. Warm sunlight enters through a large window, creating soft golden reflections on the wooden floor. A few pairs of shoes are scattered near the entrance, with a small bench and coat rack in the background. A completely different male character appears: a slim-to-average build man in his early 30s with short slightly messy brown hair, light stubble, casual gray hoodie, dark joggers, and white sneakers. He should look like an ordinary everyday person, not a fitness model. Preserve his face, hairstyle, clothing, body proportions, and overall appearance consistently throughout the entire animation. The advertisement should feel like a natural short-form social media ad, with the character speaking directly and casually rather than acting like a professional commercial presenter. [0–3 seconds] Begin with a medium-wide cinematic shot. The man walks into the apartment after spending several hours on his feet. He takes two steps, suddenly slows down, and looks uncomfortable. He takes off one sneaker and sits on the bench, rubbing the bottom of his foot with a slightly frustrated expression. He looks toward the camera and says naturally: "Man, my feet used to kill me after a long day." His delivery should feel conversational and believable, with natural lip movement and subtle facial animation. [3–7 seconds] Cut to a closer shot as he picks up the original factory insole from inside his sneaker and looks at it skeptically. He says: "Then I realized it wasn't even my shoes." He pulls the old insole out and places it beside the shoe. The camera gently pushes closer as he reaches for a new supportive shoe insole lying on the bench. Make the insole clearly visible and easy to understand as the hero product, with realistic cushioning, ergonomic shape, and premium material details. [7–11 seconds] Show him placing the new insole inside his sneaker. Use a smooth close-up of his hands fitting the insole naturally into the shoe. Show the insole sitting correctly inside the shoe with believable proportions and physical interaction. He puts the sneaker back on, stands up, and takes several comfortable steps across the hallway. His posture immediately looks more relaxed. He smiles slightly and says: "These made such a difference." Keep the acting subtle and realistic. Do not make the effect exaggerated or magical. [11–15 seconds] Move into a slightly closer cinematic shot as he walks confidently toward the apartment door, then turns back toward the camera. He briefly lifts one foot, showing the sneaker, and says with a relaxed smile: "Honestly, I wish I'd tried them sooner." Finish with a clean product-focused composition: the pair of supportive insoles is visible on the bench next to the sneakers while the man walks naturally into the background. Hold the final frame for a moment. Camera: Smooth cinematic dolly movement, subtle handheld-style realism, natural perspective, gentle push-ins, no rapid camera movement, no dramatic orbiting, no abrupt zooms. Lighting: Warm morning sunlight mixed with soft ambient indoor light. Cinematic shadows, realistic reflections, soft highlights on the product, premium commercial look. Audio: Natural male voice dialogue, subtle apartment ambience, quiet footsteps on wooden floor, soft fabric movement, shoe sounds, and minimal understated background music. Voice: Young adult male, friendly, slightly casual, conversational delivery. No exaggerated commercial voiceover. Lip synchronization must be accurate to every spoken word. Product: The shoe insoles must remain physically consistent throughout the scene. They should look like premium supportive orthopedic-style insoles designed for everyday comfort. Show their shape and cushioning clearly without adding logos, text, or branding unless explicitly provided. Maintain: Realistic anatomy, stable facial identity, accurate hands and fingers, correct foot placement, natural walking mechanics, believable shoe deformation, physically accurate interaction between hands, shoes, and insoles, consistent lighting, consistent character proportions, and smooth temporal continuity. Avoid: Extra characters, unrelated locations, duplicated limbs, distorted hands, floating objects, sliding feet, broken anatomy, sudden costume changes, exaggerated reactions, magical transformations, unrealistic product effects, subtitles, captions, text, logos, watermarks, or cuts to unrelated scenes.

MAX

21,356 просмотров • 1 месяц назад

The goal isn’t to make AI look perfect. It’s to make you forget you’re watching AI in the first place. Seedance 2.5 on DomoAI official Prompt A young Korean woman @[Image 1](image_1) is casually organizing her small apartment kitchen and dining area alone. (Image) provides only her face and hairstyle; She is the only person who appears throughout. @[Image 1](image_1) The environment is a compact, lived-in apartment kitchen connected to a small dining space. The room feels naturally cluttered but comfortable: a few grocery bags near the counter, dishes drying beside the sink, a half-open cabinet, a small wooden dining table with a ceramic mug and unopened mail, a dish towel hanging unevenly from the oven handle, a refrigerator covered with a few small magnets and handwritten notes, and a couple of reusable shopping bags resting near the doorway. Warm orange evening sunlight enters through partially open blinds, creating realistic patches of light across the floor and countertops. Her behavior is quiet, casual, and completely unperformed. She is simply doing ordinary household chores when she unexpectedly notices something behind the refrigerator. The sequence should feel like an authentic personal phone recording rather than a professionally produced commercial or cinematic scene. SHOT 1 — 0–2s: She wipes down the kitchen counter with a slightly damp cloth while casually moving a few everyday objects out of the way. The camera is handheld from a slightly low side angle, as if someone casually holding a phone while standing nearby. The framing is imperfect and slightly tilted. She quietly hums under her breath while cleaning. Audio: cloth rubbing against the countertop, faint refrigerator hum, distant neighborhood ambience. SHOT 2 — 2–4s: As she reaches toward the floor to pick up a reusable shopping bag, she notices something small wedged behind the refrigerator. She pauses and leans down to see it better. The camera quickly tilts downward and moves closer with a natural handheld wobble. She quietly says: "어? 저게 뭐야?" ("Huh? What's that?") Audio remains completely live and imperfect. SHOT 3 — 4–6s: She crouches beside the refrigerator and reaches one hand into the narrow gap behind it. She struggles slightly to reach the object, shifting her body and pulling the shopping bag out of the way. Her sweatshirt naturally wrinkles and moves with her body. The camera moves closer from above her shoulder, briefly losing focus before refocusing on her hand. She murmurs: "잠깐만…" ("Wait a second…") SHOT 4 — 6–8s: She finally manages to pull the object free. It is an old pair of wired earphones tangled into a small knot, clearly something she had forgotten months ago. She holds them in front of her and looks genuinely confused for a moment. She turns the earphones over in her fingers, inspecting them naturally. She says softly: "이게 왜 여기 있어?" ("Why is this here?") No exaggerated reaction. SHOT 5 — 8–10s: Close handheld shot from slightly below eye level. She suddenly recognizes the earphones and gives a small, genuine laugh. Her expression changes from confusion to amused realization. She says: "아… 예전에 쓰던 거네." ("Ah… these are the ones I used to use.") The camera gently drifts closer, with realistic smartphone autofocus briefly shifting between her face and the earphones. SHOT 6 — 10–13s: She looks around the messy kitchen and realizes there are still several things left to organize. She gives a tiny tired sigh, places the old earphones on the dining table beside the mug, then picks up the cloth again. She quietly mutters with a faint smile: "정리할 게 왜 이렇게 많아…" ("Why is there so much to clean up…") She immediately continues wiping the counter. SHOT 7 — 13–15s: The camera slowly backs away toward the entrance of the apartment, still handheld and slightly shaky. She continues casually cleaning the kitchen without acknowledging the camera. The warm evening sunlight remains visible through the blinds while the apartment feels naturally quiet and lived-in. The final moment should feel completely ordinary, as though the recording simply happened to capture a tiny unexpected discovery during a normal evening.

Sharon Riley

31,099 просмотров • 1 месяц назад

send your landing page to claude with this prompt ull get a video like this, made with code for free thank me later ↓ Ask me for: my landing page link, my brand name and logo mark, a two-part closing line (a statement, then a short italic tail), and a 15 second track (optional). A 14.5 second 3D fly-over of my landing page, 1440x1152 at 60fps. The page lies flat on a bright studio floor (#f9fbfb in the middle, #f2f3f6 in the corners) with a soft wide shadow around it and 24px rounded corners. One continuous camera, never a cut: it starts low over the hero and glides backwards down the page at one steady speed while looking up it, rises straight overhead to show the whole page as one strip, dives into the hero and lands it as a card under a two-line title. Focus is razor thin in front of the subject and almost none behind it, so everything near the lens melts. Cards float a little above the page with soft shadows; photos, chips and the testimonial lift off and stand up toward the lens as the camera passes them. Four small tiles of my logo lift off beside the hero button and stay with the film until the end card. The title is Geist 500, the italic tail Instrument Serif. Banned: cuts, crossfades, stops or surges in the glide, the camera turning or swinging sideways, zooming in and back out, glows, any text laid over the page before the end card. 14.5 seconds: flight 0-8.2s, rise 7.75-9.25s, overhead 9.25-9.47s, dive 9.47-9.97s, title card 9.97-14.5s. The camera 56° off straight-down and 1360px from the point it looks at, centred on the top half of the hero, the phone or product mockup sharp, four 32px logo tiles beside the button → 0-0.6: the glide eases in from rest → 0.1-1.35: the tiles lift, grow to 140-200px and hang just outside the page's top corners while the hero's chips rise to 60-80px and stand up 30° → 1.25-1.6: the glide doubles to cruising speed as the hero falls behind → 1.6: the second section's title passes the centre of the frame, its photos blurred near the lens → 1.35-2.7: that section's main photos lift to 100-130px and stand up 46°, two of its chips fly up to about 200px, stand up 54° and pass the left and right edges at 2.5 → 1.2-2.4: the tiles trail the camera 300px down the page, then drift out of the top → 3.0-7.3: every following section passes through at the same steady speed, each one sharp as it crosses the middle of the frame and soft below it; a logo tile drifts past the left edge close and blurred at 5.4 → 5.45-6.3: the testimonial card rises from 22 to 112px, stands up 30° and shows a 34px white edge → 7.3-8.2: the glide eases off as the footer arrives, the footer title sharp at 8.0 → 7.75-9.25: the rise, zooming out at an even rate while the tilt flattens (8.15-8.95) and the page's bottom edge settles 42px above the frame bottom → 9.25-9.47: the whole page as one centred strip, creeping 3.5% closer → 9.47-9.97: the dive, the page's top edge pinned to the frame top while it grows, everything below the hero fading out, then the top drops to y 283 so the hero lands as a 1018px wide card with 38px corners and a soft shadow; two logo tiles sit on its top corners, one crisp at the right edge, two huge soft blurs drift in at the bottom corners → 10.02: a white badge pill (logo + brand, 21px) fades in at y 44 → 10.12: line 1 at 74px, one word every 0.06s → 10.36: the italic tail at 82px in grey #8b8b92, one word every 0.05s, each word rising 16px out of a 12px blur in 0.34s → 10.6-14.5: hold, the card creeping 2% closer, the tiles drifting a few px. 1. Open my link in headless Chromium (Playwright) at 1440px wide, device scale 2, and scroll to the bottom once so lazy images and scroll animations finish. Mark the pieces that lift (cards, phone or product mockups, chips, feature photos, the testimonial, the hero button) with data-layer. Screenshot the full page with them hidden, then each piece alone on a transparent background with 28px padding, and save every piece's page position to a JSON. 2. One WebGL2 film page, 1440x1152, every frame computed from time inside seek(t): no timers, no CSS transitions. The page is a textured quad on the floor and each piece its own quad at its height, drawn lowest first with no depth buffer. Use mipmaps and 16x anisotropic filtering or the far text shimmers. 3. Drive the camera from one speed curve, never from a position key every half second. Focal length 1880px, 56° tilt, distance easing out from 1360 to 1700px and never back in, no turning. Speed down the page as a share of cruise (cruise is about 770 page px/s): 0 at 0s, 0.5 by 0.6s, held at 0.5 to 1.25s, 1.0 by 1.6s, held between 0.94 and 1.1 to 7.3s, then easing to 0.12 by 8.3s. Integrate it into the page position. 4. Depth of field per pixel: blur radius = 75 x (focus - depth) / depth in front of the focus and 6 x (depth - focus) / depth behind it, capped at 120px, 40 taps on a golden-angle disc, each tap read from a mip level matched to the blur. Keep the focus on whatever crosses the middle of the frame. 5. A lifted piece stands up by turning about its own middle, top edge rising toward the lens. Each casts a shadow on whatever is under it: the same picture in flat #1a2133, offset (0.10z, 4 + 0.36z), blurred 7 + 0.5z, 26% opacity. 6. Rise: zoom out in log scale with a smooth trapezoid speed (speeding up 7.75-8.35s, even 8.35-8.95s, slowing to a stop at 9.25s) and hand the glide over to a camera that holds the page's bottom edge at that 42px line from 8.3 to 8.65s. Dive: log scale on a quadratic ease in-out, then solve the look-at point from the pinned edge. A rounded-rect mask morphs from the full page to the hero, 24px to 38px corners. 7. Render with Playwright on the real GPU (--use-angle=d3d11 --enable-gpu --ignore-gpu-blocklist): 60fps, 16 subframes across 0.7 of a frame for motion blur, H.264 MP4. The track's hit goes on 9.97s, whooshes on 8.66 and 9.80. If you can't run code on my computer, tell me straight away that you can only make a live preview here and that the MP4 needs Claude Code. Phones or cards that fade out with transparency show whatever is behind them, so fade them into the haze colour first and only cut to transparent at the very end. Keep most lifts tiny (20-40px) and lock the page before timing anything, because any change in a section's height shifts everything after it. Before the final render, measure a quick 30fps preview with optical flow: the speed down the page must never dip and the zoom must never turn into a zoom-in during the flight. Ask me for the inputs, capture my page, then show me stills at 0, 1.6, 2.5, 5, 6.5, 9.3 and 11 seconds before you render.

zero

148,676 просмотров • 9 дней назад

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.

Sharon Riley

52,132 просмотров • 3 месяцев назад

After work activities. Copy the prompt, try it out, and share the results with us here👇. Created with Omni Flash 1.1, refined with Meta Edits. Enjoy! --- Prompt Workflow: Animate this JSON Prompt storyboard image sequence, following key beats exactly in order from top to bottom, left to right. Prompt: { "core_meta": { "image_type": "4-Panel Chronological Storytelling Collage", "art_medium": "Mixed-media Digital Photography", "style_modifiers": [ "Editorial Layout", "Gen Z Aesthetic", "Subversive High-Fashion", "Cinematic Narrative", "Mixed Texture Post-Processing", "Hyper-real fashion photography" ], "overall_mood": "Rebellious, confident, raw and chaotic-chic", "vibe": "Late-night urban rebellion, after-hours fashion diary", "quality_boosters": [ "Hyper-realistic skin textures", "Visible pores and natural skin imperfections", "Film grain", "High-contrast lighting", "Detailed stainless steel reflections", "Realistic fabric tension and skin contact" ] }, "subject": { "identity": { "subject_type": "Gen Z Influencer", "gender": "Female", "age": "22", "ethnicity": "Caucasian", "description": "Elena, a trendsetter with a confident, defiant, direct gaze and a 'That Girl' meets 'Night Luxe' aesthetic, radiating pure attitude. Fictional character, not a real person." }, "anatomy_and_body": { "build_and_proportions": "Slender, athletic and toned with a flat midriff, defined hip-bones and a narrow waist, with a fuller bust that creates pronounced cleavage and natural weight. Body remains lean and tight.", "height_estimation_cm": "172", "skin_texture": "Smooth, slightly dewy with a subtle sheen from kitchen heat, realistic pores visible on chest and midriff.", "biological_features": { "vascularity_and_pigment": "Subtle warmth and flush across the chest and cheeks", "subsurface_scattering": "Natural soft glow under industrial lights, especially on the upper chest", "skin_micro_texture": "Visible skin pores, fine texture and slight sheen on the chest, cleavage and exposed midriff", "eye_complexity": "Sharp, almond-shaped eyes with dark mascara, heavy-lidded and inviting" } }, "face_and_hair": { "face_structure": "Heart-shaped face with a sharp jawline and high cheekbones.", "eyes": "Piercing dark eyes with a slight siren squint and a direct, intense stare.", "eyebrows": "Groomed, laminated-style full brows.", "lips": "Glossy, over-lined with a neutral taupe shade, slightly parted in a fashion pout.", "makeup": "Clean girl aesthetic with heavy black mascara, sharp wing-tip liner and a subtle glow on the décolletage.", "expression": "A mix of defiant smirk, open-mouthed confidence and high-fashion pout across all panels.", "hair": { "style": "Long, dark wavy hair tucked under the cap in some shots, loose, messy and cascading over one shoulder and the upper chest in others.", "color": "Deep brunette with obsidian undertones", "interaction_and_physics": "Wisps of hair escaping from under the yellow cap; strands sticking slightly to dewy skin at the neckline; motion-blurred strands in the action shot." } }, "pose_and_action": { "description": "A chronological sequence of escalating attitude: walking in, peeling off the work shirt, an extreme fashion pose, and a relaxed seated rest.", "action": "A 4-step narrative of her after-hours shift undone — from clothed worker to lace and low denim, body angled toward the camera.", "body_position": { "stance": "Varies: mid-stride with chest forward (P1), dynamic twist while peeling the shirt so the lace neckline shifts (P2), deep hip-hinge with arched back and the bust lifted and pressed together (P3), relaxed seated lean-back that shows underbust and side contour (P4).", "upper_body_and_arms": "Pushing through curtains with the chest prominent; arms raised to remove the shirt so the lace-covered bust lifts and the lower curve of the cups becomes visible; hands resting along the upper curve or lightly adjusting the lace edge; leaning back on hands with the chest forward.", "lower_body_and_legs": "Striding with hips rolling; wide stance with jeans pushed low; legs elongated and slightly parted by a low angle; seated with ankles crossed or one knee raised.", "hand_gestures": "Interacting with clothing, pulling fabric aside, one hand resting on the upper curve of the bust or sliding along the lace edge." }, "gaze_direction": "Shifting from looking away to a direct, intense lens-stare.", "accuracy_constraints": [ "Maintain consistent wardrobe across all panels", "Unbuttoned jeans sit low enough to show the full hipbones and thong straps", "Emphasize the fuller bust with clear side contour, lower cup curve and upper cleavage depending on the pose", "Clothing remains on: lace bra and thong, no full nudity" ] }, "wardrobe_and_inventory": { "clothing": { "top": { "type": "Structured, low-cut lace push-up bra shaped for maximum cleavage", "fabric": "Intricate floral lace with sheer mesh panels", "color": "Onyx Black", "details": "Underwire that lifts and separates, delicate scalloped edges along the upper curve, cups sitting slightly lower in later panels so the lower cup edge and a soft shadow at the neckline are visible. Lingerie stays on." }, "bottom": { "type": "Baggy carpenter jeans", "fabric": "Heavy light-wash denim", "color": "Pale blue with distressed hems", "details": "Fully unbuttoned and folded down past the hipbones, exposing the upper curve of a black lace thong and the lower abdomen and V-line." }, "outerwear": "A yellow branded button-up work shirt pulled open and discarded mid-motion in Panel 2, fabric in flight.", "fit_and_physics": "Baggy jeans contrast with tight, straining lace; fabric tension creates deep cleavage, side contour and a visible lower cup curve wherever the body is arched or twisted." }, "accessories": { "headwear": "Yellow 'M' branded fast-food franchise baseball cap worn slightly tilted and askew.", "held_objects_and_props": [ "Industrial freezer curtains", "Discarded work shirt held against one side of the chest", "Cardboard burger boxes" ] } } }, "environment_and_scene": { "location": { "setting_type": "Commercial Fast-Food Kitchen", "description": "A closed, dimly lit industrial kitchen after hours. Stainless steel surfaces, fryers with oil sheen, and stacked burger wrappers — cold metal against warm skin." }, "atmosphere": { "time_of_day": "Late Night / After Hours", "weather_conditions": "Indoor humid industrial heat that makes the skin glisten" }, "spatial_elements": { "foreground_elements": [ "Blue plastic freezer slats", "Motion-blurred shirt", "Stacked cardboard boxes" ], "background_elements": [ "Industrial fryers", "Steel prep tables", "Warm heat-lamp glow" ] }, "texture_details": { "environment": "Cold, brushed stainless steel vs. warm incandescent bulb glow reflecting off dewy skin at the neckline.", "materials": "Slick plastic, rough denim, delicate straining lace, matte cardboard, realistic skin." } }, "camera_and_composition": { "frame": { "aspect_ratio": "16:9", "resolution": "4k", "orientation": "Horizontal Collage" }, "composition": { "shot_type": "Multi-image collage", "camera_angle": "Varied: eye-level, low-angle looking up toward the neckline, and high-angle looking down the body.", "framing_guide": "Panel 1: tall vertical with chest prominent; Panel 2: motion-blurred action of removing the shirt with a brief side contour; Panel 3: central hero shot on the arched torso, deep cleavage and lower cup curve; Panel 4: small square polaroid of her seated and relaxed.", "perspective": "First-person photographer perspective following a clandestine after-hours fashion shoot.", "depth_and_focus": "Selective focus; deep depth of field on the hero shot with razor-sharp lace and skin texture; intentional motion blur on Panel 2.", "symmetry_and_balance": "Asymmetrical, dynamic layout with overlapping edges and organic cutouts." }, "hardware_simulation": { "camera_model": "iPhone 17 Pro Max Simulation", "lens_type": "Variable focal length", "focal_length_mm": "24mm and 13mm wide angle", "phone_visibility": "Not visible" } }, "lighting_and_color": { "lighting": { "setup_type": "Mixed Industrial and Editorial", "primary_source": "Harsh overhead fluorescent (Panel 1/2)", "secondary_source": "Warm amber heat lamps (Panel 3) grazing the underside of the bust", "direction": "Side-lit and back-lit in the hero shot to carve side contour and the lower cup curve", "shadow_quality": "Deep, inky black shadows in the raw panels that pool under the bust", "highlights": "Specular highlights on stainless steel and on the glistening upper curves of the chest", "lighting_interaction": "Reflections on metal counters and dewy skin at the cleavage" }, "color_grading": { "color_mode": "High Contrast / Vibrant", "palette": "Onyx, Light Denim Blue, Franchise Yellow, Amber, Industrial Steel Grey, warm skin tones", "color_temperature": "Contrast between cool fluorescent blues and warm heat-lamp oranges that make the skin look flushed", "contrast_curve": "S-curve for punchy, editorial blacks", "lut_application": "Modern cinematic film stock with a slight green tint in shadows" } }, "post_processing_and_fx": { "rendering": { "engine": "Photorealistic photography simulation", "approach": "Hyper-realism with analog artifacts — realistic skin, no plastic or 3D look" }, "optical_artifacts": { "chromatic_aberration": "Subtle on panel edges", "vignetting": "Heavy on the Polaroid panel", "lens_flare": "Small specular glints from the stainless steel and moist skin", "bokeh_quality": "Soft, hexagonal bokeh from kitchen indicator lights" }, "sensor_atmosphere": { "iso_noise_structure": "Fine digital grain to simulate high-ISO low-light photography", "sensor_bloom": "Glow around the heat lamps and along the upper chest curves", "air_particles_and_haze": "Subtle steam/grease haze in the air that softens distant edges" }, "imperfections_and_realism": "Motion blur in the action panel; white border and fingerprint marks on the Polaroid panel; realistic skin texture, pores and slight sheen on the chest." }, "negatives": { "artifact_suppression": [ "extra fingers", "distorted face", "mismatched clothing", "cartoonish proportions", "plastic skin", "3D render look", "animated appearance", "chubby or soft body" ], "forbid": [ "explicit g*nitalia", "full frontal n*dity", "n*dity below the waist beyond thong straps", "removed lingerie" ] }, "final_director_notes": "Keep the provocation in fashion-editorial territory. The fuller bust should read clearly in every panel through cleavage, side contour and the lower cup curve, depending on the pose. Body stays slender, toned and athletic. Everything photographic, with natural skin texture and weight. Panel 3 is the anchor: arched back, lace at full tension, deep cleavage and lower cup edge lit by warm heat lamps. The collage should feel like a secret after-hours digital diary — raw, defiant, high-fashion. Adult fictional subject, lingerie remains on." }

Dominus Pellissier

13,283 просмотров • 12 дней назад

Seedance 2.0 on MiniMax Design (H3) ===================== Prompt: Style: Photorealistic behind-the-scenes smartphone vlog footage. Faux vertical smartphone footage naturally cropped into 16:9. Authentic handheld phone aesthetic. No cinematic color grading, no HDR look, no 3D render, no game engine, no beauty filters. Feels like genuine behind-the-scenes content uploaded by a Korean idol. Lighting: Bright summer afternoon sunlight through large apartment windows gradually transitions into warm evening apartment lighting. Natural exposure fluctuations and auto white balance typical of smartphone cameras. Color: Neutral consumer smartphone color science with slightly soft contrast, mild highlight clipping near windows and natural indoor color shifts. Camera: Simulated smartphone camera filmed by another female idol member. Gentle handheld movement, natural walking motion, subtle autofocus breathing, slight rolling shutter during quick pans, occasional imperfect framing, brief focus hunting and realistic phone compression. Camera behaves like a friend casually filming, never professionally stabilized. Skin: Extremely realistic skin texture with visible pores and natural imperfections. Light everyday makeup. No skin smoothing. Acting: Gentle, elegant and soft-spoken. She smiles modestly, speaks calmly, occasionally becomes slightly shy after noticing the camera, and naturally thanks the person filming. Her personality is graceful, feminine, polite and slightly reserved. She rarely laughs loudly, instead showing warm smiles, subtle amusement and delicate facial expressions. Every movement feels refined, relaxed and effortless. Physics: Hair, clothing, towels, food, steam, water droplets and household objects all move naturally with realistic weight and momentum. Composition: Casual smartphone framing with occasional imperfect composition and spontaneous reframing. Feels like authentic dorm footage rather than planned content. Continuity: Maintain the exact same face, platinum blonde long straight hair with bangs, body proportions and identity from the reference image throughout every scene. No identity drift. Technical: Authentic 24–30fps smartphone video look with subtle compression artifacts. Final output 16:9. Audio: Natural apartment ambience only. Air conditioner humming, distant Seoul traffic, birds outside the window, cooking sounds, boiling water, frying food, dishes, footsteps, running water, toothbrush brushing, hair dryer, refrigerator hum and soft room ambience. No background music. No subtitles. Overall Mood: Warm, peaceful, elegant and comforting. Similar to a quiet behind-the-scenes dorm vlog uploaded by a Korean idol. Everything feels sincere, calming and intimate without trying to be entertaining. Character: A fictional Korean female idol in her early 20s. Long platinum blonde hair with straight bangs. Fair skin. Soft cat-like eyes. Slim figure. Graceful and feminine. She is known for her gentle personality, polite manners and calm speaking voice. She has just returned to the dorm after school and a schedule and quietly spends the rest of her summer evening. Wardrobe Continuity: CUT 1 She arrives wearing the exact sailor-style school uniform from the reference image, including the cream knit vest, blue sailor collar, blue pleated skirt, white socks and black loafers. CUT 2 She changes into an oversized white graphic T-shirt and loose black athletic shorts while cooking. CUT 3 She now wears a soft pastel blue sleeveless lounge top with white lounge shorts while eating dinner. CUT 4 The same lounge outfit while brushing her teeth. CUT 5 After washing her face she changes into luxurious white silk short pajamas featuring elegant gold piping along the collar, cuffs, chest pocket and shorts hem. The pajama set consists of a relaxed short-sleeve button-up shirt with matching silk shorts. Her hair is loosely tied back while doing skincare. CUT 6 Fresh after showering, still wearing the same white silk pajamas with gold piping. Her hair is slightly damp with a white towel resting around her neck while drying it. CUT 7 Relaxing on the sofa wearing the elegant white silk pajamas while hugging a plush toy and drinking iced tea. CUT 8 Before bed she lets her hair down naturally, waves softly toward the camera while wearing the elegant white silk pajamas, turns off the bedroom light and closes the door. Scene: A beautiful modern luxury Korean idol dorm apartment during a peaceful summer afternoon and evening. Cozy, bright and elegant interior with tasteful furniture, skincare products, plush toys, snacks, fresh flowers, books and neatly organized living spaces. CUT 1 — Coming Home Continuous handheld shot. She unlocks the front door, quietly enters the dorm wearing the school uniform from the reference image, removes her loafers neatly, places her school bag beside the entrance, smiles softly toward the camera and bows her head slightly. Dialogue: "다녀왔어요." CUT 2 — Cooking The camera follows her into the kitchen. She washes vegetables, prepares simple Korean home cooking, fries eggs, boils ramen, tastes the soup with a spoon and smiles gently. Dialogue: "오늘 많이 배고프네요." A female member is heard faintly from another room. Female Voice: "언니~" She smiles softly. "왜?" CUT 3 — Dinner She sits quietly at the dining table. Before eating, she gently places her hands together. Dialogue: "잘 먹겠습니다." She enjoys the meal peacefully while occasionally smiling toward the camera. CUT 4 — Brushing Teeth Bathroom mirror shot. She brushes her teeth slowly before smiling shyly after making accidental eye contact with the camera. Dialogue: "이제 양치해야지." CUT 5 — Skincare Now wearing elegant white silk pajamas with gold piping. She carefully applies toner, serum and moisturizer while calmly speaking to the camera. Dialogue: "오늘 피부가 조금 좋아 보이는 것 같아요." CUT 6 — After Shower She walks out of the bathroom with slightly damp hair and a towel resting around her neck. She quietly dries her hair while looking out the apartment window at the summer sunset. Dialogue: "샤워하니까 정말 개운해." CUT 7 — Relaxing She sits comfortably on the sofa hugging a plush toy while sipping iced tea and slowly scrolling through her phone. A female member speaks softly from another room. Female Voice: "영화 볼래?" She smiles warmly. "좋아요." CUT 8 — Good Night Late evening. She walks into her bedroom carrying her phone charger and plush toy. She turns around one last time, smiles gently at the camera and gives a small wave. Dialogue: "오늘도 함께해줘서 정말 고마워요. 좋은 꿈 꾸세요." She switches off the bedroom light. The bedroom door slowly closes while the handheld camera quietly remains outside for another second before the recording naturally ends.

TSUBAKI

122,761 просмотров • 3 месяцев назад

PROMPT: Generate a continuous 15-second premium live-action broadcast TV commercial for a high-performance family kitchen blender, designed as an energetic, polished consumer-appliance advertisement emphasizing FAST BLENDING POWER. The commercial must tell a complete miniature visual story within exactly 15 seconds: a busy family needs breakfast quickly, fresh ingredients enter the blender, one touch unleashes powerful high-speed blending, a thick mixture transforms almost instantly into a perfectly smooth fruit smoothie, the family enjoys the result, and the commercial ends on a clean hero product shot with the promise: “Smooth in Seconds.” Maintain a consistent high-end contemporary commercial visual style throughout the entire sequence: photorealistic food photography, tactile ingredient detail, premium appliance surfaces, energetic but controlled camera movement, crisp natural highlights, appetizing freshness, believable family warmth, and polished broadcast-advertising finish. Shoot as if captured on an ARRI Alexa 35 cinema camera using a coordinated set of 24mm, 35mm, 50mm, 85mm, and 100mm macro cinema lenses. Preserve realistic perspective, physically plausible motion, natural depth of field, smooth highlight roll-off, subtle cinematic contrast, clean skin tones, rich food texture, controlled motion blur, and sharp product detail. The entire commercial takes place during one continuous bright weekday morning in the SAME modern family kitchen. The kitchen has warm off-white cabinetry, pale natural-oak counters, a large sunlit window frame-left, brushed stainless-steel fixtures, a small breakfast table in the background, subtle family-life details, and a clean uncluttered countertop. Warm morning sunlight enters consistently from frame-left at approximately 5200K, supplemented by soft interior fill, producing gentle directional shadows and bright natural reflections. Maintain the same architecture, counter layout, window position, furniture, appliances, background objects, lighting direction, and color palette throughout every shot. New camera angles reveal different perspectives of the same physical kitchen and must never create a different-looking location. LOCKED PRODUCT: one premium family countertop blender with a compact matte-silver motor base, black control panel, one illuminated circular speed control, large clear 1.8-liter blending pitcher, black fitted lid, stainless-steel blade assembly, sturdy black handle, and subtle unbranded front badge area. The blender’s shape, proportions, materials, controls, pitcher geometry, lid, handle, blade assembly, reflections, scale, and countertop position remain identical throughout every shot. It begins centered on the main kitchen counter and never changes location. LOCKED INGREDIENTS: fresh strawberries, banana pieces, blueberries, mango chunks, Greek yogurt, milk, and several ice cubes. Ingredients must retain recognizable colors and textures before entering the pitcher. Once added, object permanence must be respected: ingredients cannot reappear outside the blender. During blending, the mixture must transform physically and continuously from visibly chunky fruit and ice into a uniform thick pink-red smoothie. LOCKED FAMILY: a mother in her mid-30s with shoulder-length dark brown hair wearing a soft beige knit top and blue jeans; a father in his late-30s with short dark hair wearing a pale blue casual shirt; an approximately eight-year-old daughter with dark brown hair in a ponytail wearing a muted yellow T-shirt; and an approximately six-year-old son with short brown hair wearing a light green T-shirt. Preserve their exact ages, facial identity, hairstyle, wardrobe, body proportions, and appearance whenever visible. Their expressions progress naturally from hurried anticipation to impressed surprise to relaxed enjoyment. Avoid surreal food behavior, floating ingredients, impossible liquid physics, teleporting objects, changing blender geometry, inconsistent pitcher fill levels, duplicated fruit, warped hands, extra fingers, changing wardrobe, altered kitchen architecture, random background changes, excessive lens distortion, unreadable product geometry, fake plastic food textures, excessive camera shake, oversaturated grading, artificial CGI appearance, flickering light, exposure shifts, continuity resets, jumpy object positions, text artifacts, random labels, logos, watermarks, or unrelated products. 00:00–00:02.0 — OPENING PROBLEM / FAMILY MORNING RUSH. Begin with a dynamic 24mm wide establishing shot from approximately countertop height, looking diagonally across the kitchen while preserving a left-to-right spatial axis. The mother moves briskly toward the counter from frame-left as the two children wait near the breakfast area in the background, visibly eager and short on time. The father passes behind them preparing to leave. Morning sunlight streaks naturally through the frame-left window. The locked blender is already visible on the counter as the visual anchor, positioned prominently but naturally in the foreground-right. Use a smooth fast dolly-in toward the blender rather than a hard zoom. Small breakfast details suggest a busy school morning without cluttering the frame. Sound begins with subtle morning kitchen ambience, quick footsteps, a chair movement, and upbeat rhythmic music immediately establishing urgency. No spoken dialogue. 00:02.0–00:04.0 — INGREDIENT SPEED MONTAGE. Match-cut into a rapid sequence of three extremely concise food-preparation inserts totaling exactly two seconds. First, a 100mm macro close-up catches vivid strawberries and blueberries dropping into the clear pitcher, with realistic gravity, bounce, moisture, and fruit texture. Cut to banana pieces and mango chunks entering from above, maintaining the exact pitcher position and increasing fill level logically. Cut to a tight side insert as Greek yogurt, milk, and ice cubes enter last. Use crisp impact sounds synchronized with each ingredient: thump, splash, clink. Each insert changes visual information and advances the preparation; never repeat the same composition. Camera movement is minimal and precise so the speed comes primarily from editorial cutting. The blender remains OFF throughout these inserts. 00:04.0–00:05.2 — ONE-TOUCH ACTIVATION. Cut to an 85mm close-up from a low three-quarter front angle of the blender control panel. The mother’s right index finger enters naturally from frame-left and presses the illuminated circular control exactly once. Show believable fingertip compression against the control. The instant contact occurs, the control illumination brightens and the motor begins. Add a precise tactile click followed immediately by a confident rising electric motor sound. Use a subtle fast push-in timed to activation. The hand exits naturally; do not show multiple presses. 00:05.2–00:08.2 — POWER DEMONSTRATION / HERO BLENDING MOMENT. Cut to a dramatic but physically realistic 50mm close three-quarter view of the entire pitcher. The motor accelerates rapidly. Ice cubes and fruit initially tumble downward toward the stainless-steel blades, then form a powerful controlled vortex. Show the transformation continuously: recognizable strawberries, blueberries, banana, mango, yogurt, milk, and ice become progressively smaller and more integrated until the mixture turns into a completely smooth, thick pink-red smoothie. The action must communicate exceptional blending speed without supernatural physics. Condensation begins subtly on the outside of the pitcher. Tiny droplets and believable internal turbulence catch the frame-left morning light. During this three-second power demonstration, execute a controlled semicircular camera move of approximately 35 degrees around the front of the blender without crossing the established spatial axis. Begin slightly frame-left of the product and finish near frontal three-quarter. Maintain the blender base completely stable on the countertop with no unrealistic vibration or sliding. Use one brief 100mm macro insert lasting approximately 0.5 seconds to reveal the high-speed vortex and disappearing final fruit fragment, then return immediately to the matching three-quarter product angle. Sound design intensifies with a strong smooth motor whirr synchronized to the vortex, layered with the upbeat music. At approximately 00:07.6, the last visible fruit fragment disappears into the vortex. By 00:08.2 the mixture is visibly uniform, silky, and completely smooth. This transformation is the commercial’s core proof point: FAST BLENDING POWER. 00:08.2–00:09.5 — INSTANT RESULT. The motor stops cleanly. Cut to a 100mm macro beauty shot looking through the clear pitcher wall at the perfectly smooth smoothie surface settling from a gentle spiral into a glossy, uniform texture. A small central swirl collapses naturally. No chunks remain. Condensation beads on the exterior catch bright highlights. Use shallow depth of field while retaining enough pitcher edge detail to identify the product. Sound drops from the motor into a satisfying soft stop, followed by a subtle musical accent. A confident female voice-over begins: “Powerful blending…” 00:09.5–00:11.5 — POUR AND PROOF. Match the circular smoothie motion into a 50mm close-up of the mother tilting the same pitcher and pouring the thick smoothie into two clear family drinking glasses on the same countertop. The liquid forms a smooth continuous ribbon with realistic viscosity and no splashing errors. The pitcher’s remaining fill level decreases correctly. Camera tracks gently with the pour from left to right. The daughter and son appear softly out of focus beyond the glasses, watching with excited expressions. As the glasses fill, rack focus briefly from the flowing smoothie to the children’s delighted reaction. Voice-over completes: “…smooth results in seconds.” 00:11.5–00:13.0 — FAMILY PAYOFF. Cut to a warm 35mm medium shot at the breakfast counter. The two children each take one synchronized first sip from their filled glasses, then immediately exchange impressed smiles. The mother stands behind them with a relaxed satisfied expression while the father takes a filled travel cup and moves toward frame-right, suggesting the blender has saved valuable morning time. Keep performances natural rather than exaggerated. The blender remains visible in the background on its original counter position, recognizable and unchanged. Morning sunlight and the same warm neutral palette continue without variation. The music opens into a bright satisfying resolution. The daughter gives a quick authentic smile and says: “That was fast!” 00:13.0–00:15.0 — PRODUCT HERO / BRAND END FRAME. Use a clean visual match cut from the child’s smoothie glass to the locked blender standing alone in a polished hero composition on the SAME kitchen counter. Shoot on an 85mm lens at slightly below pitcher midpoint for a confident premium product perspective. The blender occupies the center-right of frame while a freshly poured smoothie glass, two strawberries, several blueberries, and one mango slice form a restrained ingredient arrangement in the lower foreground-left. These garnish ingredients are separate presentation ingredients introduced only for the hero composition and must not imply that previously blended ingredients have magically reappeared. Create a slow controlled 5% push-in during the final two seconds. Frame-left morning sunlight creates a clean edge highlight along the clear pitcher and matte-silver motor base. Maintain realistic reflections, exact product geometry, and crisp separation from the softly defocused kitchen background. At 00:13.3, introduce a clean broadcast-safe text overlay in the negative space on frame-left: “FAST BLENDING POWER” At 00:14.0, transition cleanly to the primary campaign line: “SMOOTH IN SECONDS.” Below it, smaller: “POWER FOR EVERY FAMILY MORNING.” Typography is modern, bold, minimal sans-serif, perfectly legible, horizontally aligned, broadcast-safe, with no distorted letters and no unnecessary graphical effects. Keep all typography outside the physical blender silhouette. Voice-over, confident and warm: “Fast power. Smooth mornings.” End exactly at 00:15.0 on a perfectly stable hero frame with the blender sharply resolved, smoothie glass visible, campaign line readable, music landing on a clean sonic logo accent. CAMERA AND EDITING RULES: Use motivated cuts whenever subject, visual information, camera position, action, or emotional emphasis changes. Maintain energetic medium-fast commercial pacing: wider contextual opening, rapid ingredient inserts, tactile activation close-up, high-energy blending demonstration, sensory result macro, fluid pouring shot, human reaction payoff, then a slower premium hero landing. Preserve the established 180-degree axis throughout. No camera crosses the axis unless visibly motivated, and no silent changes in object placement occur between cuts. Maintain consistent camera height for matching shot types. Screen direction remains left-to-right for preparation and family movement. Every shot must introduce new action, information, perspective, reaction, or product proof. AUDIO DESIGN: Begin with subtle morning kitchen ambience under upbeat modern percussive music. Synchronize fruit impacts, ice clinks, control click, motor acceleration, vortex intensity, motor stop, smoothie pour, drinking sounds, and final sonic logo precisely to picture. The blender motor must sound powerful but refined rather than harsh. Duck music naturally beneath the voice-over and daughter’s dialogue. No audio clipping or abrupt ambience resets between cuts. VISUAL COLOR SYSTEM: warm off-white, pale natural oak, matte silver, fresh strawberry red, blueberry blue, mango golden-yellow, and creamy smoothie pink-red. Preserve natural skin tones and realistic food saturation. Use a premium contemporary commercial grade with moderate contrast, soft highlight roll-off, clean whites, controlled blacks, and no teal-orange exaggeration. MOVEMENT AND PHYSICS: All hands interact correctly with objects. Ingredients obey gravity. Liquid volume remains continuous. The pitcher fill level increases when ingredients are added, decreases when smoothie is poured, and never resets between shots. The blender stays physically planted on the counter during operation. The motor vortex follows plausible fluid dynamics. Hair, clothing, reflections, condensation, shadows, and liquid motion react naturally. Maintain strict character consistency, product consistency, object permanence, environment continuity, lighting continuity, and forward-only time progression across the full sequence. Render the final commercial at 24 fps, 16:9 broadcast aspect ratio, UHD 3840×2160 resolution, high-bitrate cinematic master quality, natural 180-degree shutter motion blur, realistic cinema-lens behavior, subtle fine sensor texture, clean compression, no visible digital artifacts, no temporal flicker, no frame interpolation artifacts, and photorealistic high-end commercial rendering. Preserve sharp product edges and legible end-frame typography while allowing natural depth-of-field falloff. The entire finished sequence must be EXACTLY 15 seconds long. Do not extend or shorten any beat. The central visual message must be immediately understandable without dialogue: a busy family morning becomes easier because this family blender turns whole ingredients and ice into a perfectly smooth drink with exceptional speed. The emotional progression is urgency → activation → power → instant proof → family satisfaction → premium product promise. Final audience takeaway: FAST BLENDING POWER. SMOOTH IN SECONDS.

Gumvue Studio

21,837 просмотров • 3 месяцев назад