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  1. Home
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  4. NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
 
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NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results

Date Issued
2020
Author(s)
Abdelhamed, A
Indian Institute of Technology Jodhpur
Afifi, M
Timofte, R
Brown, MS
Cao, Y
Zhang, ZL
Zuo, WM
Zhang, XL
Liu, JY
Chen, WD
Wen, CY
Liu, M
Lv, SL
Zhang, YC
Pan, ZH
Li, BP
Xi, T
Fan, YW
Yu, XY
Zhang, G
Liu, JT
Han, JY
Ding, ER
Yu, SH
Park, B
Jeong, JC
Liu, S
Zong, ZY
Nan, N
Li, CH
Yang, ZL
Bao, L
Wang, SQ
Bai, DW
Lee, J
Kim, Y
Rho, K
Shin, C
Kim, S
Tang, PL
Zhao, YY
Zhou, YQ
Fan, YC
Huang, T
Li, ZH
Shah, NA
Liu, W
Yan, Q
Zhao, YZ
Mozejko, M
Latkowski, T
Treszczotko, L
Szafraniuk, M
Trojanowski, K
Wu, YH
Michelini, PN
Hu, FS
Lu, YH
Kim, S
Kim, W
Lee, J
Choi, JH
Zhussip, M
Khassenov, A
Kim, JH
Cho, H
Kansal, P
Nathan, S
Ye, ZY
Lu, XW
Wu, YQ
Yang, JX
Cao, YL
Tang, SL
Cao, YP
Maggioni, M
Marras, I
Tanay, T
Slabaugh, G
Yan, YL
Kang, M
Choi, HS
Song, K
Xu, SS
Lu, XM
Wang, TN
Lei, CX
Liu, B
Gupta, R
Kumar, V
DOI
10.1109/CVPRW50498.2020.00256
Abstract
This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the newly introduced dataset, the proposed methods and their results. The challenge is a new version of the previous NTIRE 2019 challenge on real image denoising that was based on the SIDD benchmark. This challenge is based on a newly collected validation and testing image datasets, and hence, named SIDD+. This challenge has two tracks for quantitatively evaluating image denoising performance in (1) the Bayer-pattern rawRGB and (2) the standard RGB (sRGB) color spaces. Each track similar to 250 registered participants. A total of 22 teams, proposing 24 methods, competed in the final phase of the challenge. The proposed methods by the participating teams represent the current state-of-the-art performance in image denoising targeting real noisy images. The newly collected SIDD+ datasets are publicly available at: https://bit.ly/siddplus_data.
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