基于可逆神经网络的神经辐射场水印方法
Watermarking for Neural Radiation Fields by Invertible Neural Network
AI总结：
本文提出一种基于可逆神经网络的神经辐射场水印方案，将水印嵌入训练图像并通过逆过程从多视点渲染图像中提取，同时引入图像质量增强模块以应对渲染造成的水印丢失，从而实现三维场景版权保护。
摘要：
为保护由神经辐射场表示的三维场景的版权，本文将神经辐射场水印的嵌入与提取视为一对图像变换的逆问题。提出了一种利用可逆神经网络水印技术保护神经辐射场版权的方案，该方案借助二维图像水印技术实现对三维场景的保护。该方案通过可逆网络中的前向过程将水印嵌入神经辐射场的训练图像中，并利用逆向过程从神经辐射场渲染得到的图像中提取水印，从而同时实现神经辐射场和三维场景的版权保护。由于神经辐射场的渲染过程会导致水印信息丢失，该方案引入了一个图像质量增强模块，利用神经网络对渲染图像进行恢复后再提取水印。该方案在每张训练图像中嵌入水印以训练神经辐射场，并能够从多个视点提取水印信息。仿真实验结果验证了该方法的有效性。
英文摘要：
To protect the copyright of the 3D scene represented by the neural radiation field, the embedding and extraction of the neural radiation field watermark are considered as a pair of inverse problems of image transformations. A scheme for protecting the copyright of the neural radiation field is proposed using invertible neural network watermarking, which utilizes watermarking techniques for 2D images to achieve the protection of the 3D scene. The scheme embeds the watermark in the training image of the neural radiation field through the forward process in the invertible network and extracts the watermark from the image rendered by the neural radiation field using the inverse process to realize the copyright protection of both the neural radiation field and the 3D scene. Since the rendering process of the neural radiation field can cause the loss of watermark information, the scheme incorporates an image quality enhancement module, which utilizes a neural network to recover the rendered image and then extracts the watermark. The scheme embeds a watermark in each training image to train the neural radiation field and enables the extraction of watermark information from multiple viewpoints. Simulation experimental results demonstrate the effectiveness of the method.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
