LiveNeRF: Efficient Face Replacement Through Neural Radiance Fields Integration

TL;DR

LiveNeRF introduces a real-time face replacement system using neural radiance fields that delivers high-quality visuals suitable for live streaming and interactive media, benefiting various practical applications.

Contribution

It presents a novel neural radiance field-based framework that achieves real-time face replacement at 33 FPS with improved visual quality, addressing limitations of prior methods.

Findings

Achieves 33 FPS in live face replacement

Provides superior visual quality compared to previous methods

Enables practical deployment in live streaming and interactive media

Abstract

Face replacement technology enables significant advancements in entertainment, education, and communication applications, including dubbing, virtual avatars, and cross-cultural content adaptation. Our LiveNeRF framework addresses critical limitations of existing methods by achieving real-time performance (33 FPS) with superior visual quality, enabling practical deployment in live streaming, video conferencing, and interactive media. The technology particularly benefits content creators, educators, and individuals with speech impairments through accessible avatar communication. While acknowledging potential misuse in unauthorized deepfake creation, we advocate for responsible deployment with user consent verification and integration with detection systems to ensure positive societal impact while minimizing risks.