mlsanityData to 7 Oct 2026

Towards High-fidelity 3D Talking Avatar with Personalized Dynamic Texture

arXiv 2503.00495 ↗First posted 1 Mar 2025cs.CV cs.AIcited by 5

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Abstract (arXiv)

Significant progress has been made for speech-driven 3D face animation, but most works focus on learning the motion of mesh/geometry, ignoring the impact of dynamic texture. In this work, we reveal that dynamic texture plays a key role in rendering high-fidelity talking avatars, and introduce a high-resolution 4D dataset TexTalk4D, consisting of 100 minutes of audio-synced scan-level meshes with detailed 8K dynamic textures from 100 subjects. Based on the dataset, we explore the inherent correlation between motion and texture, and propose a diffusion-based framework TexTalker to simultaneously generate facial motions and dynamic textures from speech. Furthermore, we propose a novel pivot-based style injection strategy to capture the complicity of different texture and motion styles, which allows disentangled control. TexTalker, as the first method to generate audio-synced facial motion with dynamic texture, not only outperforms the prior arts in synthesising facial motions, but also produces realistic textures that are consistent with the underlying facial movements. Project page: https://xuanchenli.github.io/TexTalk/.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 43 of its 75 references that are in the map. First posted on arXiv 1 Mar 2025.

Builds on

43 of 75 references.

References · 43

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31 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 2.

5 papers.