DISRQAD: Diffusion Image Super-Resolution Quality Assessment Dataset and Benchmark
cs.CV
Submitted: 2026-10-06
Updated: 2026-10-06
Code: https://github.com/Q-Future/Q-ReAlign
Terminology
Sources
- Quality-Aware Image-Text Alignment for Opinion-Unaware Image Quality Assessment
- SR-Ground: Image Quality Grounding for Super-Resolved Content
- How Accurate are Video Quality Models for Diffusion-Based Video Super-Resolution?
- LL-Bench: Rethinking Low-Level Vision Evaluation in the Era of Large-Scale Generative Models
- SR-Prominence: A Crowdsourced Protocol and Dataset Suite for Perceptually-Weighted Super-Resolution Artifact Evaluation
- Learning Transferable Visual Models From Natural Language Supervision
- Bridging the Perception Gap in Image Super-Resolution Evaluation
- Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels
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