Fidelity- and Perception-Aware Local Implicit Attention for Arbitrary-Scale Image Super-Resolution
Arbitrary-scale image super-resolution (ASISR) aims to reconstruct high-resolution images from low-resolution inputs over a continuous range of upscaling factors. While traditional pixel-regression approaches often produce overly smooth results that lack realistic details, recent diffusion methods can produce sharper and more realistic textures. However, these diffusion techniques frequently introduce the risk of structural hallucinations. To address these issues, we propose Fidelity- and Perception-Aware Local Implicit Attention (FPLIA), a framework that effectively integrates fidelity-oriented features into a diffusion pipeline to produce realistic and faithful reconstructions for ASISR...
| Authors | Yu-Syuan Xu, Hao-Lun Sun, Hao-Wei Chen et al. |
|---|---|
| Primary category | cs.CV |
| Published | 20 June 2026 |
| Last updated at source | 20 June 2026 |
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