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arXiv 2610.12952cs.CRcs.CV

WaveMark:面向扩散模型的鲁棒小波域图像水印

WaveMark: Robust Wavelet-Domain Image Watermarking for Diffusion Models

Queen's University(女王大学);Nanjing University(南京大学)

Jie Cao, Qi Li, Chaklam Cheong, Yutong Jin, Enze Yu, Zelin Zhang, Jianbing Ni

AI总结:

本文提出WaveMark小波域水印方法,将消息嵌入扩散模型初始噪声,通过多维度分布带密钥消息位副本提升鲁棒性,在14种攻击下对SD2.1生成图像的位准确率优于基线,可用于扩散模型生成图像的来源追踪与知识产权保护。

摘要:

图像水印可对扩散模型生成的逼真图像进行来源追踪,但当前最先进(SOTA)的去除攻击能在几乎不降低感知质量的情况下抑制嵌入信号,该漏洞限制了水印在知识产权保护和滥用归因中的有效性。本文提出WaveMark,一种新颖的小波域水印方法,将消息嵌入扩散模型的初始噪声中;为支持从受扰动载体中鲁棒恢复,WaveMark将带密钥的消息位副本分布在空间位置、小波方向和尺度上,每个载体分组四个潜在通道的系数,并通过幅度投影编码随机位,提供明确的解码余量。我们在SDP和MS-COCO Captions数据集上,针对14种攻击,基于SD2.1评估WaveMark:无攻击时WaveMark达到100.0%的位准确率(BA),图像质量与评估的基线相当;在SOTA MarkNull和MarkNull-A攻击下,其位准确率保持在88%以上,优于所有基线。

英文摘要:

Image watermarking enables provenance tracing for photorealistic images generated by diffusion models. However, state-of-the-art (SOTA) removal attacks can suppress embedded signals with little perceptual degradation. This vulnerability limits the effectiveness of watermarks for intellectual property protection and misuse attribution. We propose WaveMark, a novel wavelet-domain watermarking method that embeds messages in a diffusion model's initial noise. To support robust recovery from perturbed carriers, WaveMark distributes keyed replicas of message bits across spatial positions, wavelet orientations, and scales. Each carrier groups coefficients from four latent channels and encodes a randomized bit through magnitude projection, providing an explicit decoding margin. We evaluate WaveMark with SD2.1 on SDP and MS-COCO Captions under 14 attacks. WaveMark achieves 100.0% bit accuracy (BA) without attacks, while maintaining image quality comparable to the evaluated baselines. Under SOTA MarkNull and MarkNull-A, it retains over 88% BA, outperforming all baselines.

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。

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