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NTIRE 2025 Challenge on Image Super-Resolution ($\times$4): Methods and Results

2025-04-20 · Zheng Chen, Kai Liu, Jue Gong, Jingkai Wang, Lei Sun, Zongwei Wu, Radu Timofte, Yulun Zhang, Xiangyu Kong, Xiaoxuan Yu, Hyunhee Park, Suejin Han, Hakjae Jeon, Dafeng Zhang, Hyung-Ju Chun, Donghun Ryou, Inju Ha, Bohyung Han, Lu Zhao, Yuyi Zhang, Pengyu Yan, Jiawei Hu, Pengwei Liu, Fengjun Guo, Hongyuan Yu, Pufan Xu, Zhijuan Huang, Shuyuan Cui, Peng Guo, Jiahui Liu, Dongkai Zhang, Heng Zhang, Huiyuan Fu, Huadong Ma, Yanhui Guo, Sisi Tian, Xin Liu, Jinwen Liang, Jie Liu, Jie Tang, Gangshan Wu, Zeyu Xiao, Zhuoyuan Li, Yinxiang Zhang, Wenxuan Cai, Vijayalaxmi Ashok Aralikatti, Nikhil Akalwadi, G Gyaneshwar Rao, Chaitra Desai, Ramesh Ashok Tabib, Uma Mudenagudi, Marcos V. Conde, Alejandro Merino, Bruno Longarela, Javier Abad, Weijun Yuan, Zhan Li, Zhanglu Chen, Boyang Yao, Aagam Jain, Milan Kumar Singh, Ankit Kumar, Shubh Kawa, Divyavardhan Singh, Anjali Sarvaiya, Kishor Upla, Raghavendra Ramachandra, Chia-Ming Lee, Yu-Fan Lin, Chih-Chung Hsu, Risheek V Hiremath, Yashaswini Palani, YuXuan Jiang, Qiang Zhu, Siyue Teng, Fan Zhang, Shuyuan Zhu, Bing Zeng, David Bull, Jingwei Liao, Yuqing Yang, Wenda Shao, Junyi Zhao, Qisheng Xu, Kele Xu, Sunder Ali Khowaja, Ik Hyun Lee, Snehal Singh Tomar, Rajarshi Ray, Klaus Mueller, Sachin Chaudhary, Surya Vashisth, Akshay Dudhane, Praful Hambarde, Satya Naryan Tazi, Prashant Patil, Santosh Kumar Vipparthi, Subrahmanyam Murala, Bilel Benjdira, Anas M. Ali, Wadii Boulila, Zahra Moammeri, Ahmad Mahmoudi-Aznaveh, Ali Karbasi, Hossein Motamednia, Liangyan Li, Guanhua Zhao, Kevin Le, Yimo Ning, Haoxuan Huang, Jun Chen

This paper presents the NTIRE 2025 image super-resolution ($\times$4) challenge, one of the associated competitions of the 10th NTIRE Workshop at CVPR 2025. The challenge aims to recover high-resolution (HR) images from low-resolution (LR) counterparts generated through bicubic downsampling with a $\times$4 scaling factor. The objective is to develop effective network designs or solutions that achieve state-of-the-art SR performance. To reflect the dual objectives of image SR research, the challenge includes two sub-tracks: (1) a restoration track, emphasizes pixel-wise accuracy and ranks submissions based on PSNR; (2) a perceptual track, focuses on visual realism and ranks results by a perceptual score. A total of 286 participants registered for the competition, with 25 teams submitting valid entries. This report summarizes the challenge design, datasets, evaluation protocol, the main results, and methods of each team. The challenge serves as a benchmark to advance the state of the art and foster progress in image SR.

📄 PDF Abstract BibTeX arXiv:2504.14582

Code (2)

zhengchen1999/ntire2025_imagesr_x4 공식 구현 pytorch
zhengchen1999/ntire2024_imagesr_x4 pytorch

Tasks

Image Super-ResolutionSuper-Resolutionvalid

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