NTIRE 2023 Challenge on Image Denoising: Methods and Results.

Yawei Li,Yulun Zhang,Radu Timofte,Luc Van Gool,Zhijun Tu, Kunpeng Du, Hailing Wang,Hanting Chen,Wei Li, Xiaofei Wang,Jie Hu,Yunhe Wang,Xiangyu Kong, Jinlong Wu,Dafeng Zhang,Jianxing Zhang,Shuai Liu,Furui Bai,Chaoyu Feng,Hao Wang,Yuqian Zhang,Guangqi Shao,Xiaotao Wang,Lei Lei,Rongjian Xu,Zhilu Zhang,Yunjin Chen,Dongwei Ren,Wangmeng Zuo,Qi Wu,Mingyan Han,Shen Cheng,Haipeng Li,Ting Jiang,Chengzhi Jiang,Xinpeng Li, Jinting Luo,Wenjie Lin,Lei Yu,Haoqiang Fan,Shuaicheng Liu,Aditya Arora,Syed Waqas Zamir,Javier Vazquez-Corral,Konstantinos G. Derpanis,Michael S. Brown,Hao Li, Zhihao Zhao,Jinshan Pan,Jiangxin Dong,Jinhui Tang,Bo Yang, Jingxiang Chen,Chenghua Li,Xi Zhang,Zhao Zhang,Jiahuan Ren,Zhicheng Ji, Kang Miao,Suiyi Zhao,Huan Zheng,Yanyan Wei,Kangliang Liu,Xiangcheng Du, Sijie Liu,Yingbin Zheng,Xingjiao Wu,Cheng Jin, Rajeev Irny, Sriharsha Koundinya, Vighnesh Kamath, Gaurav Khandelwal,Sunder Ali Khowaja,Jiseok Yoon,Ik Hyun Lee,Shijie Chen,Chengqiang Zhao,Huabin Yang,Zhongjian Zhang, Junjia Huang, Yanru Zhang

CVPR Workshops（2023）

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摘要

This paper reviews the NTIRE 2023 challenge on image denoising (σ = 50) with a focus on the proposed solutions and results. The aim is to obtain a network design capable to produce high-quality results with the best performance measured by PSNR for image denoising. Independent additive white Gaussian noise (AWGN) is assumed and the noise level is 50. The challenge had 225 registered participants, and 16 teams made valid submissions. They gauge the state-of-the-art for image denoising.

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关键词

image denoising,independent additive white Gaussian noise,NTIRE 2023 challenge,PSNR

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