CopyRNeRF: Protecting the CopyRight of Neural Radiance Fields

被引:4
|
作者
Luo, Ziyuan [1 ,2 ]
Guo, Qing [3 ,4 ]
Cheung, Ka Chun [2 ,5 ]
See, Simon [2 ]
Wan, Renjie [1 ]
机构
[1] Hong Kong Baptist Univ, Dept Comp Sci, Hong Kong, Peoples R China
[2] NVIDIA, NVIDIA AI Technol Ctr, Santa Clara, CA USA
[3] Agcy Sci Res & Technol, IHPC, Singapore, Singapore
[4] Agcy Sci Res & Technol, CFAR, Singapore, Singapore
[5] Hong Kong Baptist Univ, Dept Math, Hong Kong, Peoples R China
基金
新加坡国家研究基金会;
关键词
D O I
10.1109/ICCV51070.2023.02047
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Neural Radiance Fields (NeRF) have the potential to be a major representation of media. Since training a NeRF has never been an easy task, the protection of its model copyright should be a priority. In this paper, by analyzing the pros and cons of possible copyright protection solutions, we propose to protect the copyright of NeRF models by replacing the original color representation in NeRF with a watermarked color representation. Then, a distortionresistant rendering scheme is designed to guarantee robust message extraction in 2D renderings of NeRF. Our proposed method can directly protect the copyright of NeRF models while maintaining high rendering quality and bit accuracy when compared among optional solutions. Project page: https://luo-ziyuan.github.io/copyrnerf.
引用
收藏
页码:22344 / 22354
页数:11
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