VineetVC: Adaptive Video Conferencing Under Severe Bandwidth Constraints Using Audio-Driven Talking-Head Reconstruction

• URL: http://arxiv.org/abs/2602.12758v1
• Date: Fri, 13 Feb 2026 09:37:10 GMT
• Title: VineetVC: Adaptive Video Conferencing Under Severe Bandwidth Constraints Using Audio-Driven Talking-Head Reconstruction
• Authors: Vineet Kumar Rakesh, Soumya Mazumdar, Tapas Samanta, Hemendra Kumar Pandey, Amitabha Das, Sarbajit Pal,
• Abstract summary: Intense bandwidth depletion within consumer and constrained networks has the potential to undermine the stability of real-time video conferencing.<n>This work delineates an adaptive conferencing system that integrates media delivery with a supplementary audio-driven talking-head reconstruction pathway.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Intense bandwidth depletion within consumer and constrained networks has the potential to undermine the stability of real-time video conferencing: encoder rate management becomes saturated, packet loss escalates, frame rates deteriorate, and end-to-end latency significantly increases. This work delineates an adaptive conferencing system that integrates WebRTC media delivery with a supplementary audio-driven talking-head reconstruction pathway and telemetry-driven mode regulation. The system consists of a WebSocket signaling service, an optional SFU for multi-party transmission, a browser client capable of real-time WebRTC statistics extraction and CSV telemetry export, and an AI REST service that processes a reference face image and recorded audio to produce a synthesized MP4; the browser can substitute its outbound camera track with the synthesized stream with a median bandwidth of 32.80 kbps. The solution incorporates a bandwidth-mode switching strategy and a client-side mode-state logger.

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