LiveNeRF: Efficient Face Replacement Through Neural Radiance Fields Integration
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 37 of its 50 references that are in the map. First posted on arXiv 10 Nov 2025.
Builds on
37 of 50 references.
References · 37
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25 more
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Citing papers per year: 2026: 1.
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