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arXiv · 2503.12751

R3-Avatar: Record and Retrieve Temporal Codebook for Reconstructing Photorealistic Human Avatars

Yifan Zhan·Wangze Xu·Qingtian Zhu·Muyao Niu·Mingze Ma·Yifei Liu·Zhihang Zhong·Xiao Sun·Yinqiang Zheng
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Abstract

We present R3-Avatar, incorporating a temporal codebook, to overcome the inability of human avatars to be both animatable and of high-fidelity rendering quality. Existing video-based reconstruction of 3D human avatars either focuses solely on rendering, lacking animation support, or learns a pose-appearance mapping for animating, which degrades under limited training poses or complex clothing. In this paper, we adopt a "record-retrieve-reconstruct" strategy that ensures high-quality rendering from novel views while mitigating degradation in novel poses. Specifically, disambiguating timestamps record temporal appearance variations in a codebook, ensuring high-fidelity novel-view rendering, while novel poses retrieve corresponding timestamps by matching the most similar training poses for augmented appearance. Our R3-Avatar outperforms cutting-edge video-based human avatar reconstruction, particularly in overcoming visual quality degradation in extreme scenarios with limited training human poses and complex clothing.

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Yifan Zhan, Wangze Xu, Qingtian Zhu, Muyao Niu, Mingze Ma, Yifei Liu, Zhihang Zhong, Xiao Sun, Yinqiang Zheng. 2025-03-17. R3-Avatar: Record and Retrieve Temporal Codebook for Reconstructing Photorealistic Human Avatars. https://arxiv.org/abs/2503.12751

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