AI RESEARCH
Pixel Perfect: Relational Image Quality Assessment with Spatially-Aware Distortions
arXiv CS.CV
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ArXi:2605.02863v1 Announce Type: new Traditional image quality assessment (IQA) methods rely on mean opinion scores (MOS), which are resource-intensive to collect and fail to provide interpretable, localized feedback on specific image distortions. We overcome these limitations by shifting from absolute quality prediction to a relational and directional assessment. Our approach utilizes a self-supervised synthetic distortion engine to generate