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

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arxiv 2503.12751 v1 pith:NFNL3ZKI submitted 2025-03-17 cs.CV

Yifan Zhan , Wangze Xu , Qingtian Zhu , Muyao Niu , Mingze Ma , Yifei Liu , Zhihang Zhong , Xiao Sun
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Yinqiang Zheng
This is my paper · ORCID
classification cs.CV
keywords humanposesrenderingavatarscodebooknovelr3-avatartemporal
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. 4DHumanDiff: Direct Text-to-4DGS Generation for Consistent 360-Degree Dynamic Humans

    cs.CV 2026-07 conditional novelty 6.0 of 10

    A diffusion model trained on 60,000 fitted 4D Gaussian Splatting human clips generates text-prompted, view-consistent dynamic humans directly in 4D, over 10x faster than video-first pipelines.

  2. Sequential Gaussian Avatars with Hierarchical Motion Context

    cs.CV 2024-11 conditional novelty 5.0 of 10

    A 3D Gaussian avatar model that conditions non-rigid deformation on hierarchical skeleton and vertex motion reaches state-of-the-art rendering quality on three human-capture datasets.

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