Watermarking for Neural Radiation Fields by Invertible Neural Network

Kavli Affiliate: Jia Liu

| First 5 Authors: Wenquan Sun, Jia Liu, Weina Dong, Lifeng Chen, Ke Niu

| Summary:

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.

| Search Query: ArXiv Query: search_query=au:”Jia Liu”&id_list=&start=0&max_results=3

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