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🤯 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...

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Larus Canus

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120,413 просмотров • 3 месяцев назад •via X (Twitter)

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🤯 I didn’t expect Depth to track rooftop parkour this cleanly! Used a fast climbing clip as the motion reference, then swapped in a student with twin tails and a backpack on a coastal school rooftop. The running path, wall contact, jumps, landings, and full-body continuity all hold together surprisingly well. 🌟 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. Depth opens up a lot more possibilities for parkour, climbing, martial arts, dance, and other complex full-body motion. Workflow + Prompt below 👇
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🤯 I didn’t expect Depth to track rooftop parkour this cleanly! Used a fast climbing clip as the motion reference, then swapped in a student with twin tails and a backpack on a coastal school rooftop. The running path, wall contact, jumps, landings, and full-body continuity all hold together surprisingly well. 🌟 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. Depth opens up a lot more possibilities for parkour, climbing, martial arts, dance, and other complex full-body motion. Workflow + Prompt below 👇

Larus Canus

24,613 просмотров • 3 месяцев назад

🤯 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 👇
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🤯 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 👇

Larus Canus

52,079 просмотров • 3 месяцев назад

Bruce Lee vs Chuck Norris, restaged with Mozart and Bach. The new Video Depth Anything model in FilmSpark.ai turns any video into a depth map you can use as a motion reference with Seedance 2.0. Live now in the Video Edit UI.
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Bruce Lee vs Chuck Norris, restaged with Mozart and Bach. The new Video Depth Anything model in FilmSpark.ai turns any video into a depth map you can use as a motion reference with Seedance 2.0. Live now in the Video Edit UI.

FilmSpark.ai

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🤯 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 👇
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🤯 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 👇

Larus Canus

132,472 просмотров • 3 месяцев назад

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.
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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.

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After extracting the depth video, the effect obtained by video referencing is very good. 1. Prepare the reference video 2. Extract the depth video 3. Prepare the character reference images 4. Input the extracted depth video and character reference images into seedance2, and you will get perfect results Complete workflow is below:
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After extracting the depth video, the effect obtained by video referencing is very good. 1. Prepare the reference video 2. Extract the depth video 3. Prepare the character reference images 4. Input the extracted depth video and character reference images into seedance2, and you will get perfect results Complete workflow is below:

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A reference video can explain a movement better than I ever could with a prompt That's why motion capture caught my attention in Dreamina Canvas: it lets you use character motion and spatial depth from a video as a foundation for a new scene A full month of Dreamina Basic is $1.50, with credits for up to 9 ten-second Seedance videos or 393 GPT Image 2.5 images Dreamina 2.0 is canvas-first — the new way AI video is made #Dreamina #DreaminaPartner
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A reference video can explain a movement better than I ever could with a prompt That's why motion capture caught my attention in Dreamina Canvas: it lets you use character motion and spatial depth from a video as a foundation for a new scene A full month of Dreamina Basic is $1.50, with credits for up to 9 ten-second Seedance videos or 393 GPT Image 2.5 images Dreamina 2.0 is canvas-first — the new way AI video is made #Dreamina #DreaminaPartner

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Guys, Depth Map Control now live on Mini Apps The workflow is quite easy: reference video -> depth map video -> reference image + depthvideo -> a video that follows motion and space more precisely. RT + Follow + Reply = 150 Credits in DMs (72H ONLY)
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Guys, Depth Map Control now live on Mini Apps The workflow is quite easy: reference video -> depth map video -> reference image + depthvideo -> a video that follows motion and space more precisely. RT + Follow + Reply = 150 Credits in DMs (72H ONLY)

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416,149 просмотров • 3 месяцев назад

Can we get this kind of movement, but with our character?” That's a very different challenge from simply generating a clip. Motion capture in Dreamina Canvas lets you use character motion and spatial depth from a reference video to help create a new scene. And for just $1.50, Dreamina Basic gives you a full month to explore different creative directions. Dreamina 2.0 is canvas-first, the new way AI video is made. #Dreamina #DreaminaPartner
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Can we get this kind of movement, but with our character?” That's a very different challenge from simply generating a clip. Motion capture in Dreamina Canvas lets you use character motion and spatial depth from a reference video to help create a new scene. And for just $1.50, Dreamina Basic gives you a full month to explore different creative directions. Dreamina 2.0 is canvas-first, the new way AI video is made. #Dreamina #DreaminaPartner

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Sora 2 can make a depth map, heat map, edge map and segmentation view, simultaneously in a grid. > start with a close up view of a woman in a studio, then split into a 2x2 grid showing in each cell the depth map, heat map, edge detection and segmentation of the scene
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Sora 2 can make a depth map, heat map, edge map and segmentation view, simultaneously in a grid. > start with a close up view of a woman in a studio, then split into a 2x2 grid showing in each cell the depth map, heat map, edge detection and segmentation of the scene

fofr

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🔥 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. 🎬
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🔥 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. 🎬

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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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This is Ray3.14 with Image-to-Video. Now in native 1080p, transform still images into cinematic motion. Create depth, parallax, and scene structure with detailed movement, transforming images into expressive, dimensional video with visual clarity. Available now in Dream Machine.
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Luma

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1. Reference Video -> Convert to Depth Map 2. Depth Map -> Seedance 2.0 (Reference Video) 3. Add Reference Image 4. Set Duration / Resolution / Aspect 5. Pass Audio from Reference Video -> Final 6. Hit Run
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1. Reference Video -> Convert to Depth Map 2. Depth Map -> Seedance 2.0 (Reference Video) 3. Add Reference Image 4. Set Duration / Resolution / Aspect 5. Pass Audio from Reference Video -> Final 6. Hit Run

Purz.ai

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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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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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Getting a character to move the way you imagined is harder than it looks. Dreamina Canvas has motion capture, so you can bring character motion and spatial depth from a reference video into a new scene instead of trying to explain every movement in words. A full month of Dreamina Basic is just $1.50, with credits for up to 9 ten-second Seedance videos or 393 GPT Image 2.5 images. Dreamina 2.0 is canvas-first, the new way AI video is made. #Dreamina #DreaminaPartner

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ReViV reconstructs viewer-centric human motion (body, hand, and gaze) and view-centric scene geometry (camera and depth) from a single egocentric RGB video in a unified feed-forward model. It formulates the task as learning the full joint probability distribution over multimodal signals, including RGB video, camera trajectory, gaze direction, full-body motion, hand motion, and depth. Powered by a Masked Generative Egocentric Transformer, ReViV operates within a single feed-forward architecture to simultaneously reconstruct the temporally consistent 4D reconstruction across the viewer and the view with fast inference speed. Paper Title: ReViV: Reconstructing the Viewer and the View in 4D from Monocular Project: Link:

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Built by Chaihuo Makerspace members QI LIU and Ethan Yeang. This #PhysicalAI demo combines #RealSense D455 + LingBot-Depth + #LingBot VLA V2 + Jetson AGX Thor + #LeKiwi to interact with a moving transparent bubble. Transparent objects are challenging for #RobotVision because their depth data can be noisy or incomplete. The setup: NVIDIA Robotics Jetson Thor → edge AI compute Hugging Face LeKiwi + SO-ARM → mobile manipulation D455 → RGB-D perception LingBot-Depth → depth processing LingBot VLA V2 → action decisions The result? You can actually play with a robot. A fun example of #EdgeAI, #SpatialPerception and #VLA coming together in the real world.
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Built by Chaihuo Makerspace members QI LIU and Ethan Yeang. This #PhysicalAI demo combines #RealSense D455 + LingBot-Depth + #LingBot VLA V2 + Jetson AGX Thor + #LeKiwi to interact with a moving transparent bubble. Transparent objects are challenging for #RobotVision because their depth data can be noisy or incomplete. The setup: NVIDIA Robotics Jetson Thor → edge AI compute Hugging Face LeKiwi + SO-ARM → mobile manipulation D455 → RGB-D perception LingBot-Depth → depth processing LingBot VLA V2 → action decisions The result? You can actually play with a robot. A fun example of #EdgeAI, #SpatialPerception and #VLA coming together in the real world.

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