NTIRE 2020 challenge on real image denoising: Dataset, methods and results

Abdelrahman Abdelhamed; Mahmoud Afifi; Radu Timofte; Michael S. Brown; Yue Cao; Zhilu Zhang; Wangmeng Zuo; Xiaoling Zhang; Jiye Liu; Wendong Chen; Changyuan Wen; Meng Liu; Shuailin Lv; Yunchao Zhang; Zhihong Pan; Baopu Li; Teng Xi; Yanwen Fan; Xiyu Yu; Gang Zhang; Jingtuo Liu; Junyu Han; Errui Ding; Songhyun Yu; Bumjun Park; Jechang Jeong; Shuai Liu; Ziyao Zong; Nan Nan; Chenghua Li; Zengli Yang; Long Bao; Shuangquan Wang; Dongwoon Bai; Jungwon Lee; Youngjung Kim; Kyeongha Rho; Changyeop Shin; Sungho Kim; Pengliang Tang; Yiyun Zhao; Yuqian Zhou; Yuchen Fan; Thomas Huang; Zhihao Li; Nisarg A. Shah; Wei Liu; Qiong Yan; Yuzhi Zhao; Marcin Mozejko; Tomasz Latkowski; Lukasz Treszczotko; Michal Szafraniuk; Krzysztof Trojanowski; Yanhong Wu; Pablo Navarrete Michelini; Fengshuo Hu; Yunhua Lu; Sujin Kim; Wonjin Kim; Jaayeon Lee; Jang Hwan Choi; Magauiya Zhussip; Azamat Khassenov; Jong Hyun Kim; Hwechul Cho; Priya Kansal; Sabari Nathan; Zhangyu Ye; Xiwen Lu; Yaqi Wu; Jiangxin Yang; Yanlong Cao; Siliang Tang; Yanpeng Cao; Matteo Maggioni; Ioannis Marras; Thomas Tanay; Gregory Slabaugh; Youliang Yan; Myungjoo Kang; Han Soo Choi; Kyungmin Song; Shusong Xu; Xiaomu Lu; Tingniao Wang; Chunxia Lei; Bin Liu; Rajat Gupta; Vineet Kumar

doi:10.1109/CVPRW50498.2020.00256

NTIRE 2020 challenge on real image denoising: Dataset, methods and results

Abdelrahman Abdelhamed, Mahmoud Afifi, Radu Timofte, Michael S. Brown, Yue Cao, Zhilu Zhang, Wangmeng Zuo, Xiaoling Zhang, Jiye Liu, Wendong Chen, Changyuan Wen, Meng Liu, Shuailin Lv, Yunchao Zhang, Zhihong Pan, Baopu Li, Teng Xi, Yanwen Fan, Xiyu Yu, Gang ZhangJingtuo Liu, Junyu Han, Errui Ding, Songhyun Yu, Bumjun Park, Jechang Jeong, Shuai Liu, Ziyao Zong, Nan Nan, Chenghua Li, Zengli Yang, Long Bao, Shuangquan Wang, Dongwoon Bai, Jungwon Lee, Youngjung Kim, Kyeongha Rho, Changyeop Shin, Sungho Kim, Pengliang Tang, Yiyun Zhao, Yuqian Zhou, Yuchen Fan, Thomas Huang, Zhihao Li, Nisarg A. Shah, Wei Liu, Qiong Yan, Yuzhi Zhao, Marcin Mozejko, Tomasz Latkowski, Lukasz Treszczotko, Michal Szafraniuk, Krzysztof Trojanowski, Yanhong Wu, Pablo Navarrete Michelini, Fengshuo Hu, Yunhua Lu, Sujin Kim, Wonjin Kim, Jaayeon Lee, Jang Hwan Choi, Magauiya Zhussip, Azamat Khassenov, Jong Hyun Kim, Hwechul Cho, Priya Kansal, Sabari Nathan, Zhangyu Ye, Xiwen Lu, Yaqi Wu, Jiangxin Yang, Yanlong Cao, Siliang Tang, Yanpeng Cao, Matteo Maggioni, Ioannis Marras, Thomas Tanay, Gregory Slabaugh, Youliang Yan, Myungjoo Kang, Han Soo Choi, Kyungmin Song, Shusong Xu, Xiaomu Lu, Tingniao Wang, Chunxia Lei, Bin Liu, Rajat Gupta, Vineet Kumar

Division of Mechanical and Biomedical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

52 Scopus citations

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 ~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.

Original language	English
Title of host publication	Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020
Publisher	IEEE Computer Society
Pages	2077-2088
Number of pages	12
ISBN (Electronic)	9781728193601
DOIs	https://doi.org/10.1109/CVPRW50498.2020.00256
State	Published - Jun 2020
Event	2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020 - Virtual, Online, United States Duration: 14 Jun 2020 → 19 Jun 2020

Publication series

Name	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume	2020-June
ISSN (Print)	2160-7508
ISSN (Electronic)	2160-7516

Conference

Conference	2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020
Country/Territory	United States
City	Virtual, Online
Period	14/06/20 → 19/06/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Access to Document

10.1109/CVPRW50498.2020.00256

Cite this

Abdelhamed, A., Afifi, M., Timofte, R., Brown, M. S., Cao, Y., Zhang, Z., Zuo, W., Zhang, X., Liu, J., Chen, W., Wen, C., Liu, M., Lv, S., Zhang, Y., Pan, Z., Li, B., Xi, T., Fan, Y., Yu, X., ... Kumar, V. (2020). NTIRE 2020 challenge on real image denoising: Dataset, methods and results. In Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020 (pp. 2077-2088). Article 9151047 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2020-June). IEEE Computer Society. https://doi.org/10.1109/CVPRW50498.2020.00256

Abdelhamed, Abdelrahman ; Afifi, Mahmoud ; Timofte, Radu et al. / NTIRE 2020 challenge on real image denoising : Dataset, methods and results. Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020. IEEE Computer Society, 2020. pp. 2077-2088 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops).

@inproceedings{fa0db3fa83d94a5d8eb5ca35b2607ac2,

title = "NTIRE 2020 challenge on real image denoising: Dataset, methods and results",

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 ~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.",

author = "Abdelrahman Abdelhamed and Mahmoud Afifi and Radu Timofte and Brown, {Michael S.} and Yue Cao and Zhilu Zhang and Wangmeng Zuo and Xiaoling Zhang and Jiye Liu and Wendong Chen and Changyuan Wen and Meng Liu and Shuailin Lv and Yunchao Zhang and Zhihong Pan and Baopu Li and Teng Xi and Yanwen Fan and Xiyu Yu and Gang Zhang and Jingtuo Liu and Junyu Han and Errui Ding and Songhyun Yu and Bumjun Park and Jechang Jeong and Shuai Liu and Ziyao Zong and Nan Nan and Chenghua Li and Zengli Yang and Long Bao and Shuangquan Wang and Dongwoon Bai and Jungwon Lee and Youngjung Kim and Kyeongha Rho and Changyeop Shin and Sungho Kim and Pengliang Tang and Yiyun Zhao and Yuqian Zhou and Yuchen Fan and Thomas Huang and Zhihao Li and Shah, {Nisarg A.} and Wei Liu and Qiong Yan and Yuzhi Zhao and Marcin Mozejko and Tomasz Latkowski and Lukasz Treszczotko and Michal Szafraniuk and Krzysztof Trojanowski and Yanhong Wu and Michelini, {Pablo Navarrete} and Fengshuo Hu and Yunhua Lu and Sujin Kim and Wonjin Kim and Jaayeon Lee and Choi, {Jang Hwan} and Magauiya Zhussip and Azamat Khassenov and Kim, {Jong Hyun} and Hwechul Cho and Priya Kansal and Sabari Nathan and Zhangyu Ye and Xiwen Lu and Yaqi Wu and Jiangxin Yang and Yanlong Cao and Siliang Tang and Yanpeng Cao and Matteo Maggioni and Ioannis Marras and Thomas Tanay and Gregory Slabaugh and Youliang Yan and Myungjoo Kang and Choi, {Han Soo} and Kyungmin Song and Shusong Xu and Xiaomu Lu and Tingniao Wang and Chunxia Lei and Bin Liu and Rajat Gupta and Vineet Kumar",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020 ; Conference date: 14-06-2020 Through 19-06-2020",

year = "2020",

month = jun,

doi = "10.1109/CVPRW50498.2020.00256",

language = "English",

series = "IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops",

publisher = "IEEE Computer Society",

pages = "2077--2088",

booktitle = "Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020",

}

Abdelhamed, A, Afifi, M, Timofte, R, Brown, MS, Cao, Y, Zhang, Z, Zuo, W, Zhang, X, Liu, J, Chen, W, Wen, C, Liu, M, Lv, S, Zhang, Y, Pan, Z, Li, B, Xi, T, Fan, Y, Yu, X, Zhang, G, Liu, J, Han, J, Ding, E, Yu, S, Park, B, Jeong, J, Liu, S, Zong, Z, Nan, N, Li, C, Yang, Z, Bao, L, Wang, S, Bai, D, Lee, J, Kim, Y, Rho, K, Shin, C, Kim, S, Tang, P, Zhao, Y, Zhou, Y, Fan, Y, Huang, T, Li, Z, Shah, NA, Liu, W, Yan, Q, Zhao, Y, Mozejko, M, Latkowski, T, Treszczotko, L, Szafraniuk, M, Trojanowski, K, Wu, Y, Michelini, PN, Hu, F, Lu, Y, Kim, S, Kim, W, Lee, J, Choi, JH, Zhussip, M, Khassenov, A, Kim, JH, Cho, H, Kansal, P, Nathan, S, Ye, Z, Lu, X, Wu, Y, Yang, J, Cao, Y, Tang, S, Cao, Y, Maggioni, M, Marras, I, Tanay, T, Slabaugh, G, Yan, Y, Kang, M, Choi, HS, Song, K, Xu, S, Lu, X, Wang, T, Lei, C, Liu, B, Gupta, R & Kumar, V 2020, NTIRE 2020 challenge on real image denoising: Dataset, methods and results. in Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020., 9151047, IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 2020-June, IEEE Computer Society, pp. 2077-2088, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020, Virtual, Online, United States, 14/06/20. https://doi.org/10.1109/CVPRW50498.2020.00256

NTIRE 2020 challenge on real image denoising: Dataset, methods and results. / Abdelhamed, Abdelrahman; Afifi, Mahmoud; Timofte, Radu et al.
Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020. IEEE Computer Society, 2020. p. 2077-2088 9151047 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2020-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - NTIRE 2020 challenge on real image denoising

T2 - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020

AU - Abdelhamed, Abdelrahman

AU - Afifi, Mahmoud

AU - Timofte, Radu

AU - Brown, Michael S.

AU - Cao, Yue

AU - Zhang, Zhilu

AU - Zuo, Wangmeng

AU - Zhang, Xiaoling

AU - Liu, Jiye

AU - Chen, Wendong

AU - Wen, Changyuan

AU - Liu, Meng

AU - Lv, Shuailin

AU - Zhang, Yunchao

AU - Pan, Zhihong

AU - Li, Baopu

AU - Xi, Teng

AU - Fan, Yanwen

AU - Yu, Xiyu

AU - Zhang, Gang

AU - Liu, Jingtuo

AU - Han, Junyu

AU - Ding, Errui

AU - Yu, Songhyun

AU - Park, Bumjun

AU - Jeong, Jechang

AU - Liu, Shuai

AU - Zong, Ziyao

AU - Nan, Nan

AU - Li, Chenghua

AU - Yang, Zengli

AU - Bao, Long

AU - Wang, Shuangquan

AU - Bai, Dongwoon

AU - Lee, Jungwon

AU - Kim, Youngjung

AU - Rho, Kyeongha

AU - Shin, Changyeop

AU - Kim, Sungho

AU - Tang, Pengliang

AU - Zhao, Yiyun

AU - Zhou, Yuqian

AU - Fan, Yuchen

AU - Huang, Thomas

AU - Li, Zhihao

AU - Shah, Nisarg A.

AU - Liu, Wei

AU - Yan, Qiong

AU - Zhao, Yuzhi

AU - Mozejko, Marcin

AU - Latkowski, Tomasz

AU - Treszczotko, Lukasz

AU - Szafraniuk, Michal

AU - Trojanowski, Krzysztof

AU - Wu, Yanhong

AU - Michelini, Pablo Navarrete

AU - Hu, Fengshuo

AU - Lu, Yunhua

AU - Kim, Sujin

AU - Kim, Wonjin

AU - Lee, Jaayeon

AU - Choi, Jang Hwan

AU - Zhussip, Magauiya

AU - Khassenov, Azamat

AU - Kim, Jong Hyun

AU - Cho, Hwechul

AU - Kansal, Priya

AU - Nathan, Sabari

AU - Ye, Zhangyu

AU - Lu, Xiwen

AU - Wu, Yaqi

AU - Yang, Jiangxin

AU - Cao, Yanlong

AU - Tang, Siliang

AU - Cao, Yanpeng

AU - Maggioni, Matteo

AU - Marras, Ioannis

AU - Tanay, Thomas

AU - Slabaugh, Gregory

AU - Yan, Youliang

AU - Kang, Myungjoo

AU - Choi, Han Soo

AU - Song, Kyungmin

AU - Xu, Shusong

AU - Lu, Xiaomu

AU - Wang, Tingniao

AU - Lei, Chunxia

AU - Liu, Bin

AU - Gupta, Rajat

AU - Kumar, Vineet

PY - 2020/6

Y1 - 2020/6

N2 - 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 ~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.

AB - 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 ~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.

UR - http://www.scopus.com/inward/record.url?scp=85090161528&partnerID=8YFLogxK

U2 - 10.1109/CVPRW50498.2020.00256

DO - 10.1109/CVPRW50498.2020.00256

M3 - Conference contribution

AN - SCOPUS:85090161528

T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

SP - 2077

EP - 2088

BT - Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020

PB - IEEE Computer Society

Y2 - 14 June 2020 through 19 June 2020

ER -

Abdelhamed A, Afifi M, Timofte R, Brown MS, Cao Y, Zhang Z et al. NTIRE 2020 challenge on real image denoising: Dataset, methods and results. In Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020. IEEE Computer Society. 2020. p. 2077-2088. 9151047. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). doi: 10.1109/CVPRW50498.2020.00256

NTIRE 2020 challenge on real image denoising: Dataset, methods and results

Abstract

Publication series

Conference

Bibliographical note

Access to Document

Fingerprint

Cite this