ReLIQS, a CLIP-based multiscale patch model with learned importance-guided patch selection, achieves SOTA or near-SOTA no-reference image quality scores across authentic, synthetic, AIGC, and ultra-high-resolution benchmarks while preserving original-resolution detail and keeping compute adjustable.
Visual im- portance pooling for image quality assessment.IEEE Jour- nal of Selected Topics in Signal Processing, 3(2):193–201,
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Learning Where to Look and How to Judge: Resolution-agnostic Image Quality Assessment with Quality-aware Saliency
ReLIQS, a CLIP-based multiscale patch model with learned importance-guided patch selection, achieves SOTA or near-SOTA no-reference image quality scores across authentic, synthetic, AIGC, and ultra-high-resolution benchmarks while preserving original-resolution detail and keeping compute adjustable.