SOURCE-LINKED INTELLIGENCE
Context-Aware Mutual Learning for Blind Image Inpainting and Beyond
Blind image inpainting, aiming to recover contaminated images in the case of unknown masks, is a challenging task. Motivated by the perspective of human vision and knowledge, blind image inpainting can be decomposed into two stages: mask estimation and image inpainting based on the estimated mask. The two-stage idea exhibits evident advantages in enhancing inpainting quality and augmenting the generalization capability of unknown real-world contamination by explicitly employing the estimated mask for image inpainting compared to one-stage scheme. This two-stage idea has also been intuitively i
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-13T11:33:01.000Z
First collected: 2026-09-20T12:21:05.240Z. This is not the publication date.