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Video Diffusion Avatars create controllable 3D models from single images

By PulseAugur Editorial · [1 sources] ·

Researchers have developed Video Diffusion Avatars (VDAs), a novel method for creating realistic, controllable 3D avatars from a single image. By fine-tuning video diffusion models, VDAs offer enhanced control over camera viewpoint, facial expressions, and upper-body pose, surpassing traditional 3D morphable models in expressiveness, particularly for intricate facial movements. The method addresses viewpoint bias inherent in learned expression codes and achieves efficient training on a single A100 GPU, outperforming existing single-image 3D avatar techniques in novel-view reenactment and multi-view consistency. AI

IMPACT Enables more realistic and controllable 3D avatar generation from limited input, potentially impacting virtual reality, gaming, and content creation.

RANK_REASON Research paper detailing a new method for creating 3D avatars. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Video Diffusion Avatars create controllable 3D models from single images

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Research paper detailing a new method for creating 3D avatars. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 Italiano(IT) · Simon Giebenhain, Tobias Kirschstein, Liam Schoneveld, Davide Davoli, Zhe Chen, Matthias Nie{\ss}ner ·

    Video Diffusion Avatars: Taming Video Diffusion Models into Controllable 3D Avatars

    arXiv:2610.23772v1 Announce Type: new Abstract: Video diffusion models (VDMs) trained on internet-scale data encode a rich prior on appearance, motion, and physics that is difficult to replicate with explicit 3D rendering and costly 3D data capture. We introduce Video Diffusion A…

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