App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 6

Watermarking for neural radiation fields by invertible neural network

Sun Wenquan
Liu Jia
Dong Weina
Chen Lifeng
Niu Ke
Key Laboratory of Network & Information Security under Chinese People Armed Police Force(PAP), Engineering University of PAP, Xi'an 710086, China
DOI: 10.19734/j.issn.1001-3695.2023.10.0433

Abstract

With the rapid advancement of neural radiation fields in 3D content representation, there is an urgent need to address the copyright problem surrounding 3D models of neural radiation fields focused on implicit representation. This paper tackled this issue by considering the embedding and extraction of neural radiation field watermarks as inverse problems of image transformations. It proposed a scheme for protecting the copyright of neural radiation fields using invertible neural network watermarking. This scheme utilized 2D image watermarking technology to safeguard 3D scenes. In the forward process of the invertible network, the watermark was embedded in the training image of the neural radiation field. In the reverse process, the watermark was extracted from the image rendered by the neural radiation field. This ensured copyright protection for both the neural radiation field and the 3D scene. However, the rendering process of the neural radiation field may result in the loss of watermark information. To address this, the paper introducesd an image quality enhancement module. This module utilized a neural network to recover the rendered image and subsequently extract the watermark. Simultaneously, the watermark was embedded in each training image to train the neural radiation field. This enabled the extraction of watermark information from multiple viewpoints. Experimental results demonstrate that the watermarking scheme outlined in this paper effectively achieves copyright protection and highlights the feasibility of the proposed approach.

Foundation Support

国家自然科学基金面上项目(62272478)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.10.0433
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 6

Publish History

[2024-02-01] Accepted Paper

Cite This Article

孙文权, 刘佳, 董炜娜, 等. 基于可逆神经网络的神经辐射场水印 [J]. 计算机应用研究, 2024, 41 (6). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.10.0433. (Sun Wenquan, Liu Jia, Dong Weina, et al. Watermarking for neural radiation fields by invertible neural network [J]. Application Research of Computers, 2024, 41 (6). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.10.0433. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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