AI RESEARCH
IPAD-CLIP: Teaching CLIP to Detect Image Local Perceptual Artifacts
arXiv CS.CV
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ArXi:2605.08664v1 Announce Type: new Current image quality assessment methods are heavily biased towards global distortions (e.g., noise, blur), neglecting local perceptual artifacts such as ghosting, lens flare, and moire effects. Although significant progress has been made in artifact removal, the fundamental problem of automatic artifact detection remains largely unexplored. In this paper, we formalize the Image Perceptual Artifact Detection (IPAD) task to address this gap.