New CASR Framework Enhances Arbitrary Scale Super-Resolution

Researchers have developed CASR, a novel cyclic framework designed to overcome limitations in arbitrary large-scale super-resolution (ASISR). This framework addresses the issue of cross-scale distribution shifts that typically lead to artifacts and noise at high magnification levels. By reformulating ultra-magnification as a sequence of in-distribution scale transitions, CASR ensures stable inference with a single model, even at extreme scales. The system incorporates SSAM and SARM modules to align structural distributions and restore high-frequency textures, thereby preserving self-similarity and improving generalization. AI

RANK_REASON The cluster contains an academic paper detailing a new technical framework for image super-resolution. [lever_c_demoted from research: ic=1 ai=1.0]

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• Arbitrary-Scale SR
• arXiv
• Hugging Face
• SARM
• SSAM
• Wenhao Guo

• paper
• other

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