arXiv cs.AI· Hailong Wang, Wuzheng Tan, Zixin Zhang, Xujun Fang, Fengjuan Gong·· 1 天前AI 评分29
ReliaGuard：面向来源归属与盲编辑定位的重建感知水印框架
ReliaGuard: Reconstruction-Aware Watermarking for Source Attribution and Blind Edit Localization
AI 导读
ReliaGuard 是一个重建感知水印框架，可在背景重建和后续图像处理下实现来源归属与盲编辑定位。在 300 张源图、900 个编辑案例的独立测试集上，完整输出与局部拼接输出的编辑区域 IoU 分别达 85.61% 和 94.90%，完整输出结果超出最强基线 45.02 个百分点，两种条件下标识符比特准确率均为 100%。
正文 · 原文
Abstract:Generative image editing facilitates content creation but complicates source attribution and edit verification. Existing watermarking methods combine copyright protection with tamper localization, yet background reconstruction can weaken spatial evidence even when source identifiers remain recoverable. We propose ReliaGuard, a reconstruction-aware watermarking framework for source attribution and blind edit localization. The writer optimizes keyed feature responses in both the protected image and its variational autoencoder reconstruction under image-distortion and source-preservation constraints. Using only the received image and a secret key, the reader combines watermark responses with local image context through residual evidence refinement and predicts an edit mask through native-resolution-guided multiscale reading. It is trained on complete editing outputs, locally spliced counterparts, and processed versions of both. On an independent test set of 300 source images and 900 editing cases from three image domains, our method achieves edit-region intersection-over-union scores of 85.61% for complete outputs and 94.90% for locally spliced outputs at a threshold calibrated to a nominal 1% background false-positive rate on complete outputs. The complete-output result exceeds the strongest baseline by 45.02 percentage points, while decoded identifier-bit accuracy reaches 100% in both conditions. Across seven families of image processing, the corresponding localization scores are 81.01% and 86.49%, with identifier-bit accuracies of 92.76% and 92.79%, respectively. These results support source recovery and blind edit localization under background reconstruction and subsequent image processing.
| Subjects: | Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR) |
| Cite as: | arXiv:2611.16368 [cs.CV] |
| (or arXiv:2611.16368v1 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2611.16368 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Hailong Wang [view email]
[v1]
Thu, 12 Nov 2026 06:33:37 UTC (6,197 KB)
来源：arXiv cs.AI · arxiv.org