Perceptive self-supervised learning network for noisy image watermark removal

arXiv:2403.02211v1 Announce Type: new
Abstract: Popular methods usually use a degradation model in a supervised way to learn a watermark removal model. However, it is true that reference images are difficult to obtain in the real world, as well as collected images by cameras suffer from noise. To overcome these drawbacks, we propose a perceptive self-supervised learning network for noisy image watermark removal (PSLNet) in this paper. PSLNet depends on a parallel network to remove noise and watermarks. The upper …

arxiv cs.cv image network self-supervised learning supervised learning type watermark