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NTIRE 2020 challenge on real-world image super-resolution: Methods and results

  • Andreas Lugmayr
  • , Martin Danelljan
  • , Radu Timofte
  • , Namhyuk Ahn
  • , Dongwoon Bai
  • , Jie Cai
  • , Yun Cao
  • , Junyang Chen
  • , Kaihua Cheng
  • , Se Young Chun
  • , Wei Deng
  • , Mostafa El-Khamy
  • , Chiu Man Ho
  • , Xiaozhong Ji
  • , Amin 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, Christian Micheloni, Kalpesh Prajapati, Haoyu Ren, Yong Hyeok Seo, Wan Chi Siu, Kyung Ah Sohn, Ying Tai, Rao Muhammad Umer, Shuangquan Wang, Huibing Wang, Timothy Haoning Wu, Haoning Wu, Biao Yang, Fuzhi Yang, Jaejun Yoo, Tongtong Zhao, Yuanbo Zhou, Haijie Zhuo, Ziyao Zong, Xueyi Zou, Li Wen Wang, Marie Paule Cani, Huan Yang, Jianlong Fu, Yukai Shi, Jaihyun Park, Junyeop Lee, Jeongki Min, Bokyeung Lee, Fengshuo Hu, Yanhong Wang, Jinjia Peng, Chengjie Wang, Jilin Li, Feiyue Huang, Xing Liu, Shuaijun Chen, Lei Zhao, Zhan Wang, Yuxuan Lin, Xu Jia, Qinquan Gao, Heena Patel, Vishal Chudasama, Kishor Upla, Raghavendra Ramachandra, Kiran Raja, Christoph Busch
  • ETH Zurich
  • Ajou University
  • SAIT (Samsung Advanced Institute of Technology)
  • InnoPeak Technology
  • Tencent
  • Guangdong University of Technology
  • Ltd.
  • Ulsan National Institute of Science and Technology
  • Imperial College London
  • Korea University
  • Mathematical and Algorithmic Sciences Lab
  • Laboratoire d'Informatique (LIX)
  • North China University of Technology
  • BOE Technology Group Co.Ltd.
  • and Physics University of Udine
  • Sardar Vallabhbhai National Institute of Technology
  • The Hong Kong Polytechnic University
  • Dalian Maritime Univerity
  • Tsinghua University
  • Shanghai Jiao Tong University
  • EPFL
  • Fuzhou University
  • Microsoft Research
  • Norwegian University of Science and Technology

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collectionContribution à une conférenceRevue par des pairs

Résumé

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.

langue originaleAnglais
titreProceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020
EditeurIEEE Computer Society
Pages2058-2076
Nombre de pages19
ISBN (Electronique)9781728193601
Les DOIs
étatPublié - 1 juin 2020
Evénement2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020 - Virtual, Online, États-Unis
Durée: 14 juin 202019 juin 2020

Série de publications

NomIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume2020-June
ISSN (imprimé)2160-7508
ISSN (Electronique)2160-7516

Une conférence

Une conférence2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020
Pays/TerritoireÉtats-Unis
La villeVirtual, Online
période14/06/2019/06/20

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