The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report
Bin Ren Yawei Li Nancy Mehta Radu Timofte Hongyuan Yu Cheng Wan Yuxin Hong Bingnan Han Zhuoyuan Wu Yajun Zou Yuqing Liu Jizhe Li Keji He Chao Fan Heng Zhang Xiaolin Zhang Xuanwu Yin Kunlong Zuo Bohao Liao Peizhe Xia Long Peng Zhibo Du Xin Di Wangkai Li Yang Wang Wei Zhai Renjing Pei Jiaming Guo Songcen Xu Yang Cao Zhengjun Zha Yan Wang Yi Liu Qing Wang Gang Zhang Liou Zhang Shijie Zhao Long Sun Jinshan Pan Jiangxin Dong Jinhui Tang Xin Liu Min Yan Qian Wang Menghan Zhou Yiqiang Yan Yixuan Liu Wensong Chan Dehua Tang Dong Zhou Li Wang Lu Tian Barsoum Emad Bohan Jia Junbo Qiao Yunshuai Zhou Yun Zhang Wei Li Shaohui Lin Shenglong Zhou Binbin Chen Jincheng Liao Suiyi Zhao Zhao Zhang Bo Wang Yan Luo Yanyan Wei Feng Li Mingshen Wang Yawei Li Jinhan Guan Dehua Hu Jiawei Yu Qisheng Xu Tao Sun Long Lan Kele Xu Xin Lin Jingtong Yue Lehan Yang Shiyi Du Lu Qi Chao Ren Zeyu Han Yuhan Wang Chaolin Chen Haobo Li Mingjun Zheng Zhongbao Yang Lianhong Song Xingzhuo Yan Minghan Fu Jingyi Zhang Baiang Li Qi Zhu Xiaogang Xu Dan Guo Chunle Guo Jiadi Chen Huanhuan Long Chunjiang Duanmu Xiaoyan Lei Jie Liu Weilin Jia Weifeng Cao Wenlong Zhang Yanyu Mao Ruilong Guo Nihao Zhang Qian Wang Manoj Pandey Maksym Chernozhukov Giang Le Shuli Cheng Hongyuan Wang Ziyan Wei Qingting Tang Liejun Wang Yongming Li Yanhui Guo Hao Xu Akram Khatami-Rizi Ahmad Mahmoudi-Aznaveh Chih-Chung Hsu Chia-Ming Lee Yi-Shiuan Chou Amogh Joshi Nikhil Akalwadi Sampada Malagi Palani Yashaswini Chaitra Desai Ramesh Ashok Tabib Ujwala Patil Uma Mudenagudi
This paper provides a comprehensive review of the NTIRE 2024 challenge,
focusing on efficient single-image super-resolution (ESR) solutions and their
outcomes. The task of this challenge is to super-resolve an input image with a
magnification factor of x4 based on pairs of low and corresponding
high-resolution images. The primary objective is to develop networks that
optimize various aspects such as runtime, parameters, and FLOPs, while still
maintaining a peak signal-to-noise ratio (PSNR) of approximately 26.90 dB on
the DIV2K_LSDIR_valid dataset and 26.99 dB on the DIV2K_LSDIR_test dataset. In
addition, this challenge has 4 tracks including the main track (overall
performance), sub-track 1 (runtime), sub-track 2 (FLOPs), and sub-track 3
(parameters). In the main track, all three metrics (ie runtime, FLOPs, and
parameter count) were considered. The ranking of the main track is calculated
based on a weighted sum-up of the scores of all other sub-tracks. In sub-track
1, the practical runtime performance of the submissions was evaluated, and the
corresponding score was used to determine the ranking. In sub-track 2, the
number of FLOPs was considered. The score calculated based on the corresponding
FLOPs was used to determine the ranking. In sub-track 3, the number of
parameters was considered. The score calculated based on the corresponding
parameters was used to determine the ranking. RLFN is set as the baseline for
efficiency measurement. The challenge had 262 registered participants, and 34
teams made valid submissions. They gauge the state-of-the-art in efficient
single-image super-resolution. To facilitate the reproducibility of the
challenge and enable other researchers to build upon these findings, the code
and the pre-trained model of validated solutions are made publicly available at
https://github.com/Amazingren/NTIRE2024_ESR/.