CopyRNeRF: Protecting the CopyRight of Neural Radiance Fields
Authors: name: Ziyuan Luo; name: Qing Guo; name: Ka Chun Cheung; name: Simon See; name: Renjie Wan
Published: 2023-07-21 12:14:33

Abstract: 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 distortion-resistant 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.