CopyRNeRF: Protecting the CopyRight of Neural Radiance Fields
This addresses the copyright protection issue for creators and users of NeRF models, which is an incremental improvement in a specific domain.
The paper tackles the problem of protecting the copyright of Neural Radiance Fields (NeRF) models by proposing a method that replaces the original color representation with a watermarked one and uses a distortion-resistant rendering scheme for robust message extraction in 2D renderings, achieving high rendering quality and bit accuracy.
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.