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The Fourth Challenge on Image Super-Resolution (×\times4) at NTIRE 2026: Benchmark Results and Method Overview

Zheng Chen
Kai Liu
Jingkai Wang
Xianglong Yan
Jianze Li
Ziqing Zhang
Jue Gong
Jiatong Li
Lei Sun
Xiaoyang Liu
Radu Timofte
Yulun Zhang
Jihye Park
Yoonjin Im
Hyungju Chun
Hyunhee Park
MinKyu Park
Zheng Xie
Xiangyu Kong
Weijun Yuan
Zhan Li
Qiurong Song
Luen Zhu
Fengkai Zhang
Xinzhe Zhu
Junyang Chen
Congyu Wang
Yixin Yang
Zhaorun Zhou
Jiangxin Dong
Jinshan Pan
Shengwei Wang
Jiajie Ou
Baiang Li
Sizhuo Ma
Qiang Gao
Jusheng Zhang
Jian Wang
Keze Wang
Yijiao Liu
Yingsi Chen
Hui Li
Yu Wang
Congchao Zhu
Saeed Ahmad
Ik Hyun Lee
Jun Young Park
Ji Hwan Yoon
Kainan Yan
Zian Wang
Weibo Wang
Shihao Zou
Chao Dong
Wei Zhou
Linfeng Li
Jaeseong Lee
Jaeho Chae
Jinwoo Kim
Seonjoo Kim
Yucong Hong
Zhenming Yan
Junye Chen
Ruize Han
Song Wang
Yuxuan Jiang
Chengxi Zeng
Tianhao Peng
Fan Zhang
David Bull
Tongyao Mu
Qiong Cao
Yifan Wang
Youwei Pan
Leilei Cao
Xiaoping Peng
Wei Deng
Yifei Chen
Wenbo Xiong
Xian Hu
Yuxin Zhang
Xiaoyun Cheng
Yang Ji
Zonghao Chen
Zhihao Xue
Junqin Hu
Nihal Kumar
Snehal Singh Tomar
Klaus Mueller
Surya Vashisth
Prateek Shaily
Jayant Kumar
Hardik Sharma
Ashish Negi
Sachin Chaudhary
Akshay Dudhane
Praful Hambarde
Amit Shukla
Shijun Shi
Jiangning Zhang
Yong Liu
Main:8 Pages
6 Figures
Bibliography:5 Pages
1 Tables
Abstract

This paper presents the NTIRE 2026 image super-resolution (×\times4) challenge, one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026. The challenge aims to reconstruct high-resolution (HR) images from low-resolution (LR) inputs generated through bicubic downsampling with a ×\times4 scaling factor. The objective is to develop effective super-resolution solutions and analyze recent advances in the field. To reflect the evolving objectives of image super-resolution, the challenge includes two tracks: (1) a restoration track, which emphasizes pixel-wise fidelity and ranks submissions based on PSNR; and (2) a perceptual track, which focuses on visual realism and evaluates results using a perceptual score. A total of 194 participants registered for the challenge, with 31 teams submitting valid entries. This report summarizes the challenge design, datasets, evaluation protocol, main results, and methods of participating teams. The challenge provides a unified benchmark and offers insights into current progress and future directions in image super-resolution.

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