用注意力引导的扩散模型，精准擦除网页图像水印同时保真度高
Saliency-Aware Diffusion Reconstruction for Effective Invisible Watermark Removal
- 根据图像重要区域注入针对性噪声，水印去除更精准
- 在多种主流水印技术下均实现强破坏力与高画质平衡
- 适合需要安全移除水印的网页内容处理场景
随着数字内容日益普及，现有水印嵌入技术因鲁棒性不足，亟需高效可靠的水印移除方法。本文提出一种新颖的显著性感知扩散重建框架（SADRE），用于网络图像水印消除。该框架结合自适应噪声注入、区域特异性扰动与先进的基于扩散的重建机制。SADRE通过显著性掩码引导，在潜在表示中注入目标噪声以破坏嵌入水印，同时保留关键图像特征。逆扩散过程实现高保真图像恢复，自适应噪声强度由水印强度决定。理论分析提供稳定性保证，实证评估表明，SADRE在多种前沿水印技术下均显著优于现有方法，有效平衡水印破坏力与图像质量。该框架为真实网络内容提供了灵活且可靠的水印消除方案。代码已公开于 https://github.com/inzamamulDU/SADRE。
原文摘要 · Abstract (English)
As digital content becomes increasingly ubiquitous, the need for robust watermark removal techniques has grown due to the inadequacy of existing embedding techniques, which lack robustness. This paper introduces a novel Saliency-Aware Diffusion Reconstruction (SADRE) framework for watermark elimination on the web, combining adaptive noise injection, region-specific perturbations, and advanced diffusion-based reconstruction. SADRE disrupts embedded watermarks by injecting targeted noise into latent representations guided by saliency masks although preserving essential image features. A reverse diffusion process ensures high-fidelity image restoration, leveraging adaptive noise levels determined by watermark strength. Our framework is theoretically grounded with stability guarantees and achieves robust watermark removal across diverse scenarios. Empirical evaluations on state-of-the-art (SOTA) watermarking techniques demonstrate SADRE's superiority in balancing watermark disruption and image quality. SADRE sets a new benchmark for watermark elimination, offering a flexible and reliable solution for real-world web content. Code is available on~\href{https://github.com/inzamamulDU/SADRE}{\textbf{https://github.com/inzamamulDU/SADRE}}.
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