LiveNeRF: Efficient Face Replacement Through Neural Radiance Fields Integration

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.

• Publication year

  2025

• Venue

  arXiv.org

• Publication date

  2025-11-10

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.48550/arXiv.2511.07552arXiv 2511.07552
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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