NeRF in NeRF: An Implicit Representation Watermark Algorithm for NeRF

Abstract

The Neural Radiation Field (NeRF) has achieved significant results in the field of computer vision. However, training NeRF models requires a large amount of computing resources and training data. Once the model is stolen or abused by illegal users, it may cause huge losses to copyright owners. This article proposes a watermarking framework for copyright protection using Implicit Neural Representation (INR). After implicitly representing the watermark information, we embed the network representing the watermark information into the network of the NeRF model by designing a specific key. The copyright verifier extracts the watermark from the NeRF model using the key to prove the copyright of the NeRF model. To our knowledge, this is the first time INR has been introduced into the copyright protection of the NeRF model. The experimental results show that our method not only has high robustness and maintains good 3D reconstruction quality, but also achieves lossless (100%) extraction of watermark information, effectively protecting the copyright of the NeRF model.