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Deep Unfolding Network for Image Super-Resolution
openaccess.thecvf.comSingle image super-resolution (SISR) refers to the pro-cess of recovering the natural and sharp detailed high-resolution(HR) counterpart from a low-resolution (LR) im-age. It is one of the classical ill-posed inverse problems in low-level computer vision and has a wide range of real-world applications, such as enhancing the image visual
![arXiv:2105.05633v1 [cs.CV] 12 May 2021](/cache/preview/6/1/2/8/2/0/d/8/thumb-612820d8df3e5b009babe51cf11c5c25.jpg)
arXiv:2105.05633v1 [cs.CV] 12 May 2021
arxiv.org1. Introduction Semantic segmentation is a challenging computer vi-sion problem with a wide range of applications includ-ing autonomous driving, robotics, augmented reality, im-age editing, medical imaging and many others [26,27,43]. The goal of semantic segmentation is to assign each im-age pixel to a category label corresponding to the under-