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NTIRE 2024 Challenge on Image Super-Resolution ($\times$4): Methods and Results

Authors :
Chen, Zheng
Wu, Zongwei
Zamfir, Eduard
Zhang, Kai
Zhang, Yulun
Timofte, Radu
Yang, Xiaokang
Yu, Hongyuan
Wan, Cheng
Hong, Yuxin
Huang, Zhijuan
Zou, Yajun
Huang, Yuan
Lin, Jiamin
Han, Bingnan
Guan, Xianyu
Yu, Yongsheng
Zhang, Daoan
Yin, Xuanwu
Zuo, Kunlong
Hao, Jinhua
Zhao, Kai
Yuan, Kun
Sun, Ming
Zhou, Chao
An, Hongyu
Zhang, Xinfeng
Song, Zhiyuan
Dong, Ziyue
Zhao, Qing
Xu, Xiaogang
Wei, Pengxu
Dou, Zhi-chao
Wang, Gui-ling
Hsu, Chih-Chung
Lee, Chia-Ming
Chou, Yi-Shiuan
Korkmaz, Cansu
Tekalp, A. Murat
Wei, Yubin
Yan, Xiaole
Li, Binren
Chen, Haonan
Zhang, Siqi
Chen, Sihan
Joshi, Amogh
Akalwadi, Nikhil
Malagi, Sampada
Yashaswini, Palani
Desai, Chaitra
Tabib, Ramesh Ashok
Patil, Ujwala
Mudenagudi, Uma
Sarvaiya, Anjali
Choksy, Pooja
Joshi, Jagrit
Kawa, Shubh
Upla, Kishor
Patwardhan, Sushrut
Ramachandra, Raghavendra
Hossain, Sadat
Park, Geongi
Uddin, S. M. Nadim
Xu, Hao
Guo, Yanhui
Urumbekov, Aman
Yan, Xingzhuo
Hao, Wei
Fu, Minghan
Orais, Isaac
Smith, Samuel
Liu, Ying
Jia, Wangwang
Xu, Qisheng
Xu, Kele
Yuan, Weijun
Li, Zhan
Kuang, Wenqin
Guan, Ruijin
Deng, Ruting
Zhang, Zhao
Wang, Bo
Zhao, Suiyi
Luo, Yan
Wei, Yanyan
Khan, Asif Hussain
Micheloni, Christian
Martinel, Niki
Publication Year :
2024

Abstract

This paper reviews the NTIRE 2024 challenge on image super-resolution ($\times$4), highlighting the solutions proposed and the outcomes obtained. The challenge involves generating corresponding high-resolution (HR) images, magnified by a factor of four, from low-resolution (LR) inputs using prior information. The LR images originate from bicubic downsampling degradation. The aim of the challenge is to obtain designs/solutions with the most advanced SR performance, with no constraints on computational resources (e.g., model size and FLOPs) or training data. The track of this challenge assesses performance with the PSNR metric on the DIV2K testing dataset. The competition attracted 199 registrants, with 20 teams submitting valid entries. This collective endeavour not only pushes the boundaries of performance in single-image SR but also offers a comprehensive overview of current trends in this field.<br />Comment: NTIRE 2024 webpage: https://cvlai.net/ntire/2024. Code: https://github.com/zhengchen1999/NTIRE2024_ImageSR_x4

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2404.09790
Document Type :
Working Paper