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Poster

Protecting NeRFs' Copyright via Plug-And-Play Watermarking Base Model

Qi Song · Ziyuan Luo · Ka Chun Cheung · Simon See · Renjie Wan

# 337
Strong blind review: This paper was not made available on public preprint services during the review process Strong Double Blind
[ ] [ Paper PDF ]
Fri 4 Oct 1:30 a.m. PDT — 3:30 a.m. PDT

Abstract:

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. This paper introduces a plug-and-play method to protect NeRF's copyright during its creation. We propose utilizing a pre-trained watermarking base model, enabling NeRF creators to embed binary messages directly while creating their NeRF. Our plug-and-play property ensures that 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 methods. Our code will be released upon the acceptance of this paper.

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