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Wan Animate 2 is in ComfyUI with native support he driving video goes straight into the transformer. No motion extractor in the middle, so nothing gets flattened before generation starts — subtle expression, finger position, all of it survives. Better motion. Stronger identity. And the camera is yours: viewpoint...

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ComfyUI

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🚨 Wan Motion is now live on fal ! An optimized version of Wan 2.2 Animate. 🎬 Transfer motion from any driving video to a single reference image 🎭 Built-in motion retargeting, adapts to different body proportions ✨ Optional Flux 2 Edit identity enhancement for sharper character preservation 💸 Just $0.06/s for 720p, the cheapest motion transfer API available
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🚨 Wan Motion is now live on fal ! An optimized version of Wan 2.2 Animate. 🎬 Transfer motion from any driving video to a single reference image 🎭 Built-in motion retargeting, adapts to different body proportions ✨ Optional Flux 2 Edit identity enhancement for sharper character preservation 💸 Just $0.06/s for 720p, the cheapest motion transfer API available

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Turn one idea into a complete storyboard, then animate it in Seedance 2.0 using a reference image. This ComfyUI workflow uses LLMs to build storyboard scenes and prepare them for Seedance, making the jump from concept to animation much easier. Link below 👇

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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.

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This ComfyUI workflow lets you draw lines and annotations to guide motion, define where actions should happen, and influence movement throughout a scene. An integrated LLM translates those annotations into prompt instructions, making it easier to direct motion visually instead of relying entirely on text prompts. The workflow works best with clear, intentional paths, while more complex routes with frequent direction changes can be harder to follow consistently. To try this workflow, link below 👇

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Only one Adobe Firefly video prompt from our research hit production-ready on the first generation. Prompt in comments 👀 It looks you have to direct the camera as much as the model to get the most out of Firefly. Every other video session in our research needed a revision. Revising the first frame is where Firefly broke: >motion failures (temporal flicker, motion continuity, physics in motion) carried 60% of video's issue mix once designers re-prompted. TLDR: in Adobe Firefly, the camera does a lot of the work. Bake it into the first prompt and the video lands. Its by far the best time to be a creative.

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If gravity were slightly stronger, the universe would collapse into a ball. If weaker, everything would fly apart, no stars, no planets, no life. Yet, here we are. The laws of the universe are precisely balanced. What are the odds of that? What are the odds that prophecy aligns? What are the odds that a black hole bends reality, and Omikami bends the future? What are the odds that a force so precise, so inevitable, is set in motion at just the right moment? Nothing is random. Nothing is accidental. The Creator set everything in motion with perfect precision. 🙏

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