The Tenth NTIRE 2025 Image Denoising Challenge Report
Abstract
This paper presents an overview of the NTIRE 2025 Image Denoising Challenge (\sigma = 50), highlighting the proposed methodologies and corresponding results. The primary objective is to develop a network architecture capable of achieving high-quality denoising performance, quantitatively evaluated using PSNR, without constraints on computational complexity or model size. The task assumes independent additive white Gaussian noise (AWGN) with a fixed noise level of 50. A total of 290 participants registered for the challenge, with 20 teams successfully submitting valid results, providing insights into the current state-of-the-art in image denoising.
Cite
Text
Sun et al. "The Tenth NTIRE 2025 Image Denoising Challenge Report." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025.Markdown
[Sun et al. "The Tenth NTIRE 2025 Image Denoising Challenge Report." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025.](https://mlanthology.org/cvprw/2025/sun2025cvprw-tenth/)BibTeX
@inproceedings{sun2025cvprw-tenth,
title = {{The Tenth NTIRE 2025 Image Denoising Challenge Report}},
author = {Sun, Lei and Guo, Hang and Ren, Bin and Van Gool, Luc and Timofte, Radu and Li, Yawei},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2025},
pages = {1342-1369},
url = {https://mlanthology.org/cvprw/2025/sun2025cvprw-tenth/}
}