AI RESEARCH
OARS: Process-Aware Online Alignment for Generative Real-World Image Super-Resolution
arXiv CS.CV
•
ArXi:2603.12811v1 Announce Type: new Aligning generative real-world image super-resolution models with human visual preference is challenging due to the perception--fidelity trade-off and diverse, unknown degradations. Prior approaches rely on offline preference optimization and static metric aggregation, which are often non-interpretable and prone to pseudo-diversity under strong conditioning.