ResGuard: Enhancing Robustness Against Known Original Attacks in Deep Watermarking
Deep learning-based image watermarking commonly adopts an "Encoder-Noise Layer-Decoder" (END) architecture to improve robustness against random channel distortions, yet it often overlooks intentional manipulations introduced by adversaries with additional knowledge. In this paper, we revisit this paradigm and expose a critical yet underexplored vulnerability: the Known Original Attack (KOA), where an adversary has access to multiple original-watermarked image pairs, enabling various targeted suppression strategies. We show that even a simple residual-based removal approach, namely estimating an embedding residual from known pairs and subtracting it from unseen watermarked images, can almo...
| Authors | Hanyi Wang, Han Fang, Yupeng Qiu et al. |
|---|---|
| Primary category | cs.CV |
| Published | 4 April 2026 |
| Last updated at source | 4 April 2026 |
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