NTIRE 2023 Challenge on Image Denoising: Methods and Results

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 Gaussia...

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Main Authors: Li, Yawei, Zhang, Yulun, Timofte, Radu, Gool, Luc Van, Tu, Zhijun, Du, Kunpeng, Wang, Hailing, Chen, Hanting, Li, Wei, Wang, Xiaofei, Hu, Jie, Wang, Yunhe, Kong, Xiangyu, Wu, Jinlong, Zhang, Dafeng, Zhang, Jianxing, Liu, Shuai, Bai, Furui, Feng, Chaoyu, Wang, Hao, Zhang, Yuqian, Shao, Guangqi, Wang, Xiaotao, Lei, Lei, Xu, Rongjian, Zhang, Zhilu, Chen, Yunjin, Ren, Dongwei, Zuo, Wangmeng, Wu, Qi, Han, Mingyan, Cheng, Shen, Li, Haipeng, Jiang, Ting, Jiang, Chengzhi, Li, Xinpeng, Luo, Jinting, Lin, Wenjie, Yu, Lei, Fan, Haoqiang, Liu, Shuaicheng, Arora, Aditya, Zamir, Syed Waqas, Vazquez-Corral, Javier, Derpanis, Konstantinos G., Brown, Michael S., Li, Hao, Zhao, Zhihao, Pan, Jinshan, Dong, Jiangxin, Tang, Jinhui, Yang, Bo, Chen, Jingxiang, Li, Chenghua, Zhang, Xi, Zhang, Zhao, Ren, Jiahuan, Ji, Zhicheng, Miao, Kang, Zhao, Suiyi, Zheng, Huan, Wei, YanYan, Liu, Kangliang, Du, Xiangcheng, Liu, Sijie, Zheng, Yingbin, Wu, Xingjiao, Jin, Cheng, Irny, Rajeev, Koundinya, Sriharsha, Kamath, Vighnesh, Khandelwal, Gaurav, Khowaja, Sunder Ali, Yoon, Jiseok, Lee, Ik Hyun, Chen, Shijie, Zhao, Chengqiang, Yang, Huabin, Zhang, Zhongjian, Huang, Junjia, Zhang, Yanru
Format: Conference Proceeding
Language:English
Subjects:
Atmospheric measurements
AWGN
Computer vision
Conferences
Image denoising
Particle measurements
Pattern recognition
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Summary: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.
ISSN:2160-7516
DOI:10.1109/CVPRW59228.2023.00188