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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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25,141 views • 3 days ago •via X (Twitter)

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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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Real Human support for Seedance 2.0 is now available in ComfyUI. Unlock real human video generation with Seedance 2.0 now in ComfyUI. This unlocks real-person video generation with consistent identity and authentic facial expressions — after a one-time verification.
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Real Human support for Seedance 2.0 is now available in ComfyUI. Unlock real human video generation with Seedance 2.0 now in ComfyUI. This unlocks real-person video generation with consistent identity and authentic facial expressions — after a one-time verification.

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How to animate a photo with Grok imagine : 1-import the photo in Grok imagine 2-Click on Animate That's it ! And the result is sublime. See video 👍 Original photo below⏬
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The Grok Imagine updates keep accelerating. Reference-to-Video + Video Extend just landed! Live in ComfyUI on Day 0. The generation speed alone makes it worth trying. Reference-to-Video: add up to 7 reference images to generate consistent characters and scenes Video Extend: seamlessly extend any video with smooth, natural motion Workflows and more details about the Grok updates below ⬇️

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The next frontier in AI video isn't better motion - it's better perspective. What used to require a full production setup, camera rig, location scout, multi-shot choreography - now starts with a single image inside Comfy. Creator seungho__yeo ( IG ) used Hyper POV + Seedance 2 to build a complete cinematic space traversal from one still frame: → Aggressive first-person orbit through the full environment → Fly-through movement that inhabits the space, not just records it → Motion blur and single-take continuity that holds the cinematic feel end to end → No cuts. No rig. One image as the source of truth. This is what perspective design looks like at the new baseline.

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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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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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73,884 views • 2 months ago

Eye gaze fully fixed in Comfy now for Wan Animate. All you need to do is use the pre processing nodes I linked in the first comment below for your pose / face crop. Tested this against Wan's Native source code and it is indeed 1:1 functioning now this was 300+ frames
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Eye gaze fully fixed in Comfy now for Wan Animate. All you need to do is use the pre processing nodes I linked in the first comment below for your pose / face crop. Tested this against Wan's Native source code and it is indeed 1:1 functioning now this was 300+ frames

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You can create split-stack videos like this in one click with the link below.👇 In the simple version, all you have to do is upload an image and it handles everything for you. But if you want more control, you can jump into graph mode and tweak each parameter to get more detailed, custom results.
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You can create split-stack videos like this in one click with the link below.👇 In the simple version, all you have to do is upload an image and it handles everything for you. But if you want more control, you can jump into graph mode and tweak each parameter to get more detailed, custom results.

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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 👇
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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 👇

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33,901 views • 2 months ago

Using Blender camera animation with Seedance 2.0 gives you a lot more control over your shots. By keyframing the camera in Blender, you can precisely define movement, rotation, and framing, then bring that motion into Seedance. It's a great workflow for previs-style blockouts or any shot where intentional camera movement matters. To try this workflow, link below 👇
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Using Blender camera animation with Seedance 2.0 gives you a lot more control over your shots. By keyframing the camera in Blender, you can precisely define movement, rotation, and framing, then bring that motion into Seedance. It's a great workflow for previs-style blockouts or any shot where intentional camera movement matters. To try this workflow, link below 👇

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A guy from China is reshaping glowing particles into a jellyfish, a statue, a dragon, and a samurai just by moving his hands in front of a camera No controller, no mouse, no keyboard Just a camera reading his hand position and a particle system recalculating thousands of points in real time, morphing one shape straight into the next Clench both fists at the end, and everything collapses into nothing This is running live at 60fps, not pre-rendered The entire scene sits inside a wireframe box tracking every motion as raw geometry reshapes into whatever his hands tell it to become

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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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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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85,184 views • 28 days ago

LTX-2.3 is now supported in ComfyUI Major quality improvements from Lightricks: - Finer visual details - Better 9:16 portrait videos - Cleaner audio - More stable image-to-video motion - Smarter prompt understanding - Clearer text rendering Examples 🧵👇
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LTX-2.3 is now supported in ComfyUI Major quality improvements from Lightricks: - Finer visual details - Better 9:16 portrait videos - Cleaner audio - More stable image-to-video motion - Smarter prompt understanding - Clearer text rendering Examples 🧵👇

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53,339 views • 5 months ago

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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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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44,319 views • 1 month ago

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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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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12,847 views • 2 months ago

Krea 2 is back and this time the weights are OPEN. This open source release ships with two models designed to work together — Krea 2 RAW and Krea 2 Turbo. RAW is for training, Turbo is for inference.
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Krea 2 is back and this time the weights are OPEN. This open source release ships with two models designed to work together — Krea 2 RAW and Krea 2 Turbo. RAW is for training, Turbo is for inference.

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32,394 views • 1 month ago

🎉 The built-in node help menu is now available to everyone. 🔁 Just update your ComfyUI to the latest version and make sure the frontend is at least v1.22.2
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🎉 The built-in node help menu is now available to everyone. 🔁 Just update your ComfyUI to the latest version and make sure the frontend is at least v1.22.2

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16,738 views • 1 year ago

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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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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34,424 views • 1 year ago