🤯 Depth videos perfectly solve false flags on reference... videos — and can perfectly recreate both martial arts and dance! Turned a Guan Dao martial arts clip into a Depth motion reference, swapped the fighter for a market auntie, and moved the scene to a T-junction inside a local market 🤣 🌟 Workflow: 1. Pick a reference clip under 15 seconds 2. Convert it to Depth with Depth Anything V2 3. Generate a new character + scene 4. Feed everything into Seedance with the prompt below 🌟 Depth video conversion: You can build a local Depth converter with Codex — prompt in the comments. This goes way beyond trending dances. Martial arts, polearms, and other complex movements can all be transferred cleanly with Depth! Workflow + Prompt below 👇show more

🤯 Depth can now recreate complex climbing and parkour... motion this cleanly! Turned a fast climbing clip into a Depth motion reference, then swapped in a 20-year-old twin-tail student with a backpack while keeping the same concrete structure. Wall contact, weight shifts, jumps, climbing paths, and full-body movement all stay surprisingly clean and consistent! 🌟 Workflow: 1. Pick a reference clip under 15 seconds 2. Convert it to Depth with Depth Anything V2 3. Generate a new character + scene 4. Feed everything into Seedance with the prompt below 🌟 Depth video conversion: You can build a local Depth converter with Codex — prompt in the comments. Dance, martial arts, climbing, parkour, and other complex movements can all be transferred cleanly with Depth! Workflow + Prompt below 👇show more

A new stable motion transfer workflow for Seedance 2.0!... We built a video-to-depth-video + skeleton-binding Skill based on "Depth-Anything-V2" for motion transfer. Tell your agent to help me create a Skill that converts a normal video into a depth video with skeleton binding. Motion transfer can be achieved with only the following prompt + content description:show more

Depth video workflows have been getting a lot of... attention lately, so I tested one myself. Combined with Seedance 2.0, it produced more natural motion-transfer results than using Kling Motion Control directly. Why use a depth video? 1. It removes the original character and scene details, reducing copyright and sensitive-content risks. 2. It preserves the original motion, timing, and spatial structure. This separates motion extraction from visual generation, allowing you to recreate the movement with better models and any reference character. We’ve also launched a free online tool that converts regular videos into depth videos—no local setup required: In the example below, we converted a dance video from Douyin into a depth video, then regenerated it with a reference character using Seedance 2.0. The original choreography and timing are preserved, while the lighting adapts naturally to the new character and scene.show more

🤯 Found another great use case for Depth today!... I tried recreating this fashion transformation video with my own character, but the original character kept showing up. 🌟 So I switched the reference video to Depth, and it worked way better! Same motion and timing, but now I can use my own character and completely new outfits! Quick workflow in the comments Full Depth workflow in the quoted post 👇show more

New fal workflow: video restyling with Video Depth Anything... and Seedance 2.0 - Restyle the first frame into your target look - Extract consistent depth across the source video - Use that depth to guide Seedance 2.0 through the full sequence - Preserve the original motion and composition while transforming the visual style A simple workflow for turning existing footage into stylized video.show more

THE DEPTH MAP TRICK THAT FIXED DANCE ACCURACY IN... SEEDANCE 2.0 Feed the model a video of someone dancing and it tries to interpret everything- the person, the clothes, the lighting, the room, and somewhere in there, the movement. Feed it a depth map and there's nothing left to interpret but the motion. Most creators trying to transfer a dance to a character reference the source footage directly, then wonder why the choreography drifts. The problem isn't the model - it's that you handed it ten variables when you only wanted one. Here's the workflow 1. Lock the character reference in GPT Image 2 first -face, build, costume, so identity holds independently of whatever motion gets applied to it 2. Convert the source dance footage into a depth map instead of using the raw video -this strips out the original performer's appearance, clothing, and environment entirely 3. Feed the depth map as the motion reference and the character sheet as the identity reference- two separate inputs doing two separate jobs, not one input trying to do both 5. Let the depth map carry only spatial movement -the model receives body position and momentum with no competing information about who's moving or what they look like 6. Keep the character and motion inputs isolated throughout - the moment you mix appearance data into the motion reference, the model starts negotiating between two identities Why this works • Raw footage passes the model everything at once- performer, wardrobe, room, lighting -and the choreography competes with all of it for attention • A depth map is pure spatial information, so the only thing left to transfer is movement • Separating identity from motion means the character can stay locked while the dance stays accurate - normally you're trading one for the other • The accuracy gain isn't the model getting better, it's the model getting fewer decisions to make Use cases: ⁃ Dance and choreography transfer onto original characters ⁃ Motion capture-style workflows without motion capture ⁃ Any sequence where a specific movement needs to survive intact ⁃ Character showcase content built on existing performance footage The character sheet answers who's dancing. The depth map answers how - and keeping those two questions separate is the whole trick.show more

THE DEPTH MAP TRICK THAT FIXED DANCE ACCURACY IN... SEEDANCE 2.0 Feed the model a video of someone dancing and it tries to interpret everything- the person, the clothes, the lighting, the room, and somewhere in there, the movement. Feed it a depth map and there's nothing left to interpret but the motion. Most creators trying to transfer a dance to a character reference the source footage directly, then wonder why the choreography drifts. The problem isn't the model - it's that you handed it ten variables when you only wanted one. Here's the workflow 1. Lock the character reference in GPT Image 2 first -face, build, costume, so identity holds independently of whatever motion gets applied to it 2. Convert the source dance footage into a depth map instead of using the raw video -this strips out the original performer's appearance, clothing, and environment entirely 3. Feed the depth map as the motion reference and the character sheet as the identity reference- two separate inputs doing two separate jobs, not one input trying to do both 5. Let the depth map carry only spatial movement -the model receives body position and momentum with no competing information about who's moving or what they look like 6. Keep the character and motion inputs isolated throughout - the moment you mix appearance data into the motion reference, the model starts negotiating between two identities Why this works • Raw footage passes the model everything at once- performer, wardrobe, room, lighting -and the choreography competes with all of it for attention • A depth map is pure spatial information, so the only thing left to transfer is movement • Separating identity from motion means the character can stay locked while the dance stays accurate - normally you're trading one for the other • The accuracy gain isn't the model getting better, it's the model getting fewer decisions to make Use cases: ⁃ Dance and choreography transfer onto original characters ⁃ Motion capture-style workflows without motion capture ⁃ Any sequence where a specific movement needs to survive intact ⁃ Character showcase content built on existing performance footage The character sheet answers who's dancing. The depth map answers how - and keeping those two questions separate is the whole trick.show more

OpenArt just launched Seedance 2.0 for Teams and Enterprise... It delivers the kind of camera control, reference depth, and cinematic storytelling most AI video tools still struggle to offer You can use up to 9 image references, 3 videos, and 3 audio files to build multi-shot scenes with far more control than a normal prompt 10 prompts worth saving:show more

🔥 AI video creation is finally evolving beyond basic... motion prompts. Try out Depth Map Control right here: Historically, the hardest part of the process has been maintaining scene consistency: • camera movement • object placement • spatial relationships Thanks to PixVerse Depth Map Control, you can now grab depth data from a reference video and merge it with a fresh image to explore highly directed video generation. The final outcome? Much smoother camera tracking. Highly cohesive visual scenes. It is a powerful workflow that hands creators actual authority over how their AI visuals shift and flow over time. 🎬show more

Create a short film like this in just 1... minute with GPT Image 2.0 + Seedance 2.0. GPT Image 2.0 can naturally combine multiple photos into one single image, while Seedance 2.0 can use that image as a reference to automatically separate the scenes, generate a coherent video sequence, and add suitable background music. This workflow greatly improves the overall creative efficiency. When using this method, simply provide the merged image as a reference for Seedance 2.0 and briefly describe each scene with a simple prompt. This can significantly increase the success rate of the final video. All of the above was created on GPT Image Prompt: Seedance Prompt:show more

Turn a simple idea into a storyboard, then generate... the video with Seedance 2.0. This ComfyUI workflow uses LLMs to structure prompts into storyboard-ready scenes that define how the video should play out. The storyboard can be paired with reference images and sent directly into Seedance for video generation. To try this workflow, link below 👇show more

Diving into a new hobby? 🧠 With Gemini Deep... Research you can build an in-depth & personalized beginner's guide on nearly anything you're curious about. Just select Deep Research from the prompt bar or model picker dropdown to get started and let Gemini do the research for you:show more

Let's create a music video with these characters. Used... the Midjourney images directly into Seedance 2.0 and added the track I created in Suno as a blackout video reference. You can find the prompt below.show more

🔥 If I tell you this is how I... create my characters, don't believe me. With this prompt, you can turn your character reference into a 15 second creation process video. From rough sketch to final render, the whole build comes together on screen inside a drawing UI. MiniMax H3 - You can find the prompt below.show more

Create the viral “girlfriend opens the door” video with... GPT Image 2 + local MiniMax H3. 1️⃣ Use GenVizu Canvas Mode to generate the character and scene reference images. 2️⃣ Use my ComfyUI node to turn a simple prompt into a structured 6-part H3 prompt. 3️⃣ Wait & Enjoy! ✨show more

MiniMax H3 is now on Magnific and honestly, there’s... a lot you can do with it. You can mix text, images, videos and audio in a single prompt up to 9 images, 3 videos and 3 audio references. Start creating now: It can generate up to 15s of 2K video with synced sound, including voice, music and effects. And you can go beyond generation too: edit clips, remove objects, transfer motion, and control the camera, character and voice. But the multi-reference workflow is probably my favorite. Give it your product, character, environment and motion references, and H3 pulls everything together. It feels like a much easier way to go from an idea to an actual finished video.show more

Seedance 2 ile dövüş sanatları videosu:🥊 1. Referans combat... choreography sheet’i yükle 📄 2. Karakter / savaşçı görselini yükle 🖤 3. Hareketleri tek promptla akıt 🎬 9 adımlık dövüş planı ➜ kesintisiz aksiyon videosu 🔥 Guard stance → jab → cross punch → spinning kick finish 🚀 Prompt takibi gerçekten başka seviye. Prompt: 👇 Create a seamless 15-second women’s combat sports choreography video using the uploaded 9-step martial arts reference sheet only for movement order and body-action structure. REFERENCE IMAGE: Use the 9-step martial arts sheet only as choreography reference. Do not recreate the sheet, text, arrows, numbers, or panel layout. MOVEMENT STYLE: Smooth, athletic, feminine, stylish, and continuous. The routine should feel like a choreographed martial arts flow, not separate tutorial poses. Every move should naturally connect to the next.show more

Just made this with Seedance. Full workflow, start to... finish: - Grab a reference image — TikTok, Instagram, or Pinterest - Upload it to Claude, write a JSON prompt, adjust as you like - Generate the image - Upload it to Seedance 2.5 with your full video prompt Done All inside MakeUGC, for $1. I made a full guide breaking down the exact JSON prompt structure that makes this work. Comment "JSON" and I'll send it overshow more

GPT image 2.0 combined with Seedance 2.0 is changing... how animated videos are created. With a single prompt like the one below , AI can generate an entire storyboard and turn it into a cinematic 2D animation, complete with expressive characters, smooth motion, realistic physics, comedy, and perfectly timed action.show more

🤯 K-pop meets a full-on water obstacle challenge! 🌊... Made with Seedance in a Korean variety show style Full workflow: 1. 4:3 character sheet for the girl, swimsuit and expressions 2. 3:1 wide course image for the pool set, audience and obstacles 3. Seedance image-to-video for the full run and final splash From the confident start to the final fall, the character and scene consistency held up really well! Workflow + Prompt in the comments 👇show more