面向神经辐射场的水印算法

Watermarking for neural radiance field

针对隐式表示的3D模型的版权保护问题,提出了一种面向神经辐射场(NeRF)的水印算法。该算法通过嵌入网络对训练集中的图像嵌入水印,再利用NeRF模型进行3D模型建模。版权验证方通过给定一个秘密视角作为神经辐射场的输入,生成新视角下的图像作为后门图像,接着利用神经网络的过参数化方法设计一个水印提取器,获取该视角下嵌入的水印图像。在黑盒场景下,一旦怀疑3D模型被未经授权地使用,验证方则可以通过秘密视角提取水印以验证网络版权。实验结果表明,所提算法提取水印不仅具有良好的视觉效果,而且对不同类型的噪声攻击具有较好的抵抗能力。

This paper proposed a watermarking algorithm for neural radiance fields(NeRF)to address the copyright protection issue of implicit 3D models.The algorithm embedded watermarks into the images in the training set through an embedding network,and then utilized the NeRF model for 3D model modeling.It generated a backdoor image by the copyright verifier from a new perspective by providing a secret perspective as input to the neural radiation field.Subsequently,it designed a watermark extractor using the hyperparameterization method of the neural network to obtain the embedded watermark image from that perspective.In a black box scenario,once there was suspicion of unauthorized use of the 3D model,the verifier could extract watermarks from a secret perspective to verify network copyright.The experimental results demonstrate that the proposed algorithm not only yields good visual effects when extracting watermarks,but also exhibits robust resistance to different types of noise attacks.