面向扩散模型的图像水印方法研究综述OA

The rapid development of diffusion models increasingly blurs the boundary between real and AI-generated images.This trend triggers critical issues regarding content authenticity,accountability,and copyright protection,and urgently de-mands reliable watermarking techniques for verification and traceability.To assist researchers,this review systematically sur-veyed watermarking methods for diffusion models.Firstly,the paper outlined the advancements of various watermarking app-roaches from the perspective of embedding stages and mechanisms and constructed a watermark classification framework tailo-red for diffusion models.Secondly,it analyzed generative watermarking mechanisms based on fine-tuning and initial noise,comparing their respective strengths and limitations.Furthermore,the study clarified the application scenarios of watermarks in intellectual property protection,AI-generated content(AIGC)traceability,and accountability,and summarized an evaluation system that covered imperceptibility,robustness,and watermark capacity.Finally,the review explored current challenges and future development directions for image watermarking in diffusion models and provides potential solutions.