This paper introduces a generative 3D video conferencing system using pre-trained Neural Radiance Field (NeRF) models for high-fidelity 3D head reconstruction and real-time rendering.
Video conferencing, is the most demanding form of video communication in terms of real-time requirements and it remains a challenge to maintain quality in weak network conditions. Traditional block-based encoding video conferencing systems can experience freezing and significant degradation when bandwidth is extremely low or network conditions deteriorate suddenly. Recent advancements in 3D facial representation offer novel promising solutions for video conferencing under weak network conditions.
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