NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
/ Authors
Andreas Lugmayr, Martin Danelljan, R. Timofte, Namhyuk Ahn, Dongwoon Bai, Jie Cai, Yun Cao, Junyang Chen, Kaihua Cheng, S. Chun
and 36 more authors
Wei Deng, Mostafa El-Khamy, C. Ho, Xiaozhong Ji, A. Kheradmand, Gwantae Kim, Hanseok Ko, Kanghyu Lee, Jungwon Lee, Hao Li, Ziluan Liu, Zhi-Song Liu, Shuai Liu, Yunhua Lu, Zibo Meng, Pablo Navarrete Michelini, C. Micheloni, Kalpesh P. Prajapati, Haoyu Ren, Y. Seo, W. Siu, Kyung-ah Sohn, Ying Tai, Rao Muhammad Umer, Shuangquan Wang, Huibing Wang, T. Wu, Haoning Wu, Biao Yang, Fuzhi Yang, Jaejun Yoo, Tongtong Zhao, Yuanbo Zhou, Haijie Zhuo, Ziyao Zong, Xueyi Zou
/ Abstract
This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting, where paired true high and low-resolution images are unavailable. For training, only one set of source input images is therefore provided along with a set of unpaired high-quality target images. In Track 1: Image Processing artifacts, the aim is to super-resolve images with synthetically generated image processing artifacts. This allows for quantitative benchmarking of the approaches w.r.t. a ground-truth image. In Track 2: Smartphone Images, real low-quality smart phone images have to be super-resolved. In both tracks, the ultimate goal is to achieve the best perceptual quality, evaluated using a human study. This is the second challenge on the subject, following AIM 2019, targeting to advance the state-of-the-art in super-resolution. To measure the performance we use the benchmark protocol from AIM 2019. In total 22 teams competed in the final testing phase, demonstrating new and innovative solutions to the problem.
Journal: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)