CopyRNeRF：保护神经辐射场的版权
CopyRNeRF: Protecting the CopyRight of Neural Radiance Fields
July 21, 2023
作者: Ziyuan Luo, Qing Guo, Ka Chun Cheung, Simon See, Renjie Wan
cs.AI
摘要
神经辐射场（Neural Radiance Fields，NeRF）有成为媒体主要表征的潜力。由于训练 NeRF 从未是一项简单的任务，保护其模型版权应成为首要任务。本文通过分析可能的版权保护解决方案的利弊，提议通过用带水印的颜色表示替换 NeRF 中的原始颜色表示来保护 NeRF 模型的版权。然后，设计了一种抗失真渲染方案，以确保在 NeRF 的 2D 渲染中能够稳健地提取信息。我们提出的方法可以直接保护 NeRF 模型的版权，同时在与可选解决方案相比时保持高渲染质量和比特精度。
English
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.