Research progress of AIGC image watermarking technology based on diffusion model

Xinting Wu, Ying Huang, Hu Guan, Baoning Niu, Jie Liu, Shuwu Zhang

Abstract: With the rapid development of artificial intelligence generated content (AIGC) technology, its application in the field of vision has brought unprecedented opportunities and challenges. This paper deeply explores the application of AIGC technology in the field of image generation, analyzes the evolution of existing image generation technology, especially the technology based on diffusion model, and explores its challenges in copyright protection and content security. In response to these problems, this paper focuses on the latest research progress of digital watermarking technology as a solution, including traditional watermarking methods and watermarking technology based on deep learning. Furthermore, this paper discusses in detail the digital watermarking technology for AIGC visual large models, including two categories: image generation model watermarking and generated image content watermarking, and analyzes their technical principles, application prospects and challenges. Finally, this paper summarizes and prospects the existing challenges and future trends of AIGC visual large

External IDs:doi:10.1145/3708657.3708733