Arbitrary-scale super-resolution via deep learning: A comprehensive survey

H Liu, Z Li, F Shang, Y Liu, L Wan, W Feng, R Timofte - Information Fusion, 2024 - Elsevier
Super-resolution (SR) is an essential class of low-level vision tasks, which aims to improve
the resolution of images or videos in computer vision. In recent years, significant progress …

Local implicit normalizing flow for arbitrary-scale image super-resolution

JE Yao, LY Tsao, YC Lo, R Tseng… - Proceedings of the …, 2023 - openaccess.thecvf.com
Flow-based methods have demonstrated promising results in addressing the ill-posed
nature of super-resolution (SR) by learning the distribution of high-resolution (HR) images …

Best of Both Worlds: Learning Arbitrary-scale Blind Super-Resolution via Dual Degradation Representations and Cycle-Consistency

SY Weng, H Yuan, YS Xu… - Proceedings of the …, 2024 - openaccess.thecvf.com
Single image super-resolution (SISR) for reconstructing from a low-resolution (LR) input
image its corresponding high-resolution (HR) output is a widely-studied research problem in …