Protecting NeRFs' Copyright via Plug-And-Play Watermarking Base Model
<|reference_start|>Protecting NeRFs' Copyright via Plug-And-Play Watermarking Base Model: Neural Radiance Fields (NeRFs) have become a key method for 3D scene representation. With the rising prominence and influence of NeRF, safeguarding its intellectual property has become increasingly important. In this paper, we propose \textbf{NeRFProtector}, which adopts a plug-and-play strategy to protect NeRF's copyright during its creation. NeRFProtector utilizes a pre-trained watermarking base model, enabling NeRF creators to embed binary messages directly while creating their NeRF. Our plug-and-play property ensures NeRF creators can flexibly choose NeRF variants without excessive modifications. Leveraging our newly designed progressive distillation, we demonstrate performance on par with several leading-edge neural rendering methods. Our project is available at: \url{https://qsong2001.github.io/NeRFProtector}.<|reference_end|>
@article{song2024protecting,
    title={Protecting NeRFs' Copyright via Plug-And-Play Watermarking Base Model},
    author={Qi Song and Ziyuan Luo and Ka Chun Cheung and Simon See and Renjie Wan},
    journal={arXiv preprint arXiv:2407.07735},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.07735},
    primaryClass={cs.CV}
}