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arXiv · 2601.21269

Lightweight High-Fidelity Low-Bitrate Talking Face Compression for 3D Video Conference

Jianglong Li·Jun Xu·Bingcong Lu·Zhengxue Cheng·Hongwei Hu·Ronghua Wu·Li Song
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Abstract

The demand for immersive and interactive communication has driven advancements in 3D video conferencing, yet achieving high-fidelity 3D talking face representation at low bitrates remains a challenge. Traditional 2D video compression techniques fail to preserve fine-grained geometric and appearance details, while implicit neural rendering methods like NeRF suffer from prohibitive computational costs. To address these challenges, we propose a lightweight, high-fidelity, low-bitrate 3D talking face compression framework that integrates FLAME-based parametric modeling with 3DGS neural rendering. Our approach transmits only essential facial metadata in real time, enabling efficient reconstruction with a Gaussian-based head model. Additionally, we introduce a compact representation and compression scheme, including Gaussian attribute compression and MLP optimization, to enhance transmission efficiency. Experimental results demonstrate that our method achieves superior rate-distortion performance, delivering high-quality facial rendering at extremely low bitrates, making it well-suited for real-time 3D video conferencing applications.

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Jianglong Li, Jun Xu, Bingcong Lu, Zhengxue Cheng, Hongwei Hu, Ronghua Wu, Li Song. 2026-01-29. Lightweight High-Fidelity Low-Bitrate Talking Face Compression for 3D Video Conference. https://arxiv.org/abs/2601.21269

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