The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report

Bin Ren, Hang Guo, Lei Sun, Zongwei Wu, Radu Timofte, Yawei Li; Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR) Workshops, 2025, pp. 917-966

Abstract

This paper presents a comprehensive review of the NTIRE 2025 Challenge on Single-Image Efficient Super-Resolution (ESR). The challenge aimed to advance the development of deep models that optimize key computational metrics, i.e., runtime, parameters, and FLOPs, while achieving a PSNR of at least 26.90 dB on the DIV2K_LSDIR_valid dataset and 26.99 dB on the DIV2K_LSDIR_test dataset. A robust participation saw 244 registered entrants, with 43 teams submitting valid entries. This report meticulously analyzes these methods and results, emphasizing groundbreaking advancements in state-of-the-art single-image ESR techniques. The analysis highlights innovative approaches and establishes benchmarks for future research in the field.

Related Material

[pdf] [arXiv]
[bibtex]
@InProceedings{Ren_2025_CVPR, author = {Ren, Bin and Guo, Hang and Sun, Lei and Wu, Zongwei and Timofte, Radu and Li, Yawei}, title = {The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report}, booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR) Workshops}, month = {June}, year = {2025}, pages = {917-966} }