NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report

Codruta O. Ancuti; Cosmin Ancuti; Florin Alexandru Vasluianu; Radu Timofte; Han Zhou; Wei Dong; Yangyi Liu; Jun Chen; Huan Liu; Liangyan Li; Zijun Wu; Yubo Dong; Yuyan Li; Tian Qiu; Yu He; Yonghong Lu; Yinwei Wu; Zhenxiang Jiang; Songhua Liu; Xingyi Yang; Yongcheng Jing; Bilel Benjdira; Anas M. Ali; Anis Koubaa; Hao Hsiang Yang; I. Hsiang Chen; Wei Ting Chen; Zhi Kai Huang; Yi Chung Chen; Chia Hsuan Hsieh; Hua En Chang; Yuan Chun Chiang; Sy Yen Kuo; Yu Guo; Yuan Gao; Ryan Wen Liu; Yuxu Lu; Jingxiang Qu; Shengfeng He; Wenqi Ren; Trung Hoang; Haichuan Zhang; Amirsaeed Yazdani; Vishal Monga; Lehan Yang; Alex Jiahao Wu; Tiancheng Mai; Xiaofeng Cong; Xuemeng Yin; Xuefei Yin; Hazim Emad; Ahmed Abdallah; Yahya Yasser; Dalia Elshahat; Esraa Elbaz; Zhan Li; Wenqing Kuang; Ziwei Luo; Fredrik K. Gustafsson; Zheng Zhao; Jens Sjölund; Thomas B. Schön; Zhao Zhang; Yanyan Wei; Junhu Wang; Suiyi Zhao; Huan Zheng; Jin Guo; Yangfan Sun; Tianli Liu; Dejun Hao; Kui Jiang; Anjali Sarvaiya; Kalpesh Prajapati; Ratnadeep Patra; Pragnesh Barik; Chaitanya Rathod; Kishor Upla; Kiran Raja; Raghavendra Ramachandra; Christoph Busch

doi:10.1109/CVPRW59228.2023.00180

NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report

Codruta O. Ancuti^*
, Cosmin Ancuti
, Florin Alexandru Vasluianu
, Radu Timofte
, Han Zhou
, Wei Dong
, Yangyi Liu
, Jun Chen
, Huan Liu
, Liangyan Li
, Zijun Wu
, Yubo Dong
, Yuyan Li
, Tian Qiu
, Yu He
, Yonghong Lu
, Yinwei Wu
, Zhenxiang Jiang
, Songhua Liu
, Xingyi Yang

Yongcheng Jing, Bilel Benjdira, Anas M. Ali, Anis Koubaa, Hao Hsiang Yang, I. Hsiang Chen, Wei Ting Chen, Zhi Kai Huang, Yi Chung Chen, Chia Hsuan Hsieh, Hua En Chang, Yuan Chun Chiang, Sy Yen Kuo, Yu Guo, Yuan Gao, Ryan Wen Liu, Yuxu Lu, Jingxiang Qu, Shengfeng He, Wenqi Ren, Trung Hoang, Haichuan Zhang, Amirsaeed Yazdani, Vishal Monga, Lehan Yang, Alex Jiahao Wu, Tiancheng Mai, Xiaofeng Cong, Xuemeng Yin, Xuefei Yin, Hazim Emad, Ahmed Abdallah, Yahya Yasser, Dalia Elshahat, Esraa Elbaz, Zhan Li, Wenqing Kuang, Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, Thomas B. Schön, Zhao Zhang, Yanyan Wei, Junhu Wang, Suiyi Zhao, Huan Zheng, Jin Guo, Yangfan Sun, Tianli Liu, Dejun Hao, Kui Jiang, Anjali Sarvaiya, Kalpesh Prajapati, Ratnadeep Patra, Pragnesh Barik, Chaitanya Rathod, Kishor Upla, Kiran Raja, Raghavendra Ramachandra, Christoph Busch

^*Corresponding author for this work

Politehnica University of Timisoara
Université catholique de Louvain
University of Würzburg
Swiss Federal Institute of Technology Zurich
McMaster University
University of Alberta
Xidian University
National University of Singapore
University of Sydney
Prince Sultan University (PSU)
National Taiwan University
Wuhan University of Technology
Singapore Management University
Sun Yat-Sen University
Pennsylvania State University
Southeast University, Nanjing
University of California at Los Angeles
Beijing Jiaotong University
Mansoura University
University of Jinan
Uppsala University
Hefei University of Technology
Zhejiang Dahua Technology Co., Ltd.
Sardar Vallabhbhai National Institute of Technology Surat
Norwegian University of Science and Technology

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

32 Scopus citations

Abstract

This study assesses the outcomes of the NTIRE 2023 Challenge on Non-Homogeneous Dehazing, wherein novel techniques were proposed and evaluated on new image dataset called HD-NH-HAZE. The HD-NH-HAZE dataset contains 50 high resolution pairs of real-life outdoor images featuring nonhomogeneous hazy images and corresponding haze-free images of the same scene. The nonhomogeneous haze was simulated using a professional setup that replicated real-world conditions of hazy scenarios. The competition had 246 participants and 17 teams submitted solutions for the final testing phase. The proposed solutions demonstrated the cutting-edge in image dehazing technology.

Original language	English
Title of host publication	Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023
Publisher	IEEE Computer Society
Pages	1808-1825
Number of pages	18
ISBN (Electronic)	9798350302493
DOIs	https://doi.org/10.1109/CVPRW59228.2023.00180
State	Published - 2023
Externally published	Yes
Event	2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023 - Vancouver, Canada Duration: 18 06 2023 → 22 06 2023

Publication series

Name	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume	2023-June
ISSN (Print)	2160-7508
ISSN (Electronic)	2160-7516

Conference

Conference	2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023
Country/Territory	Canada
City	Vancouver
Period	18/06/23 → 22/06/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Access to Document

10.1109/CVPRW59228.2023.00180

Cite this

Ancuti, C. O., Ancuti, C., Vasluianu, F. A., Timofte, R., Zhou, H., Dong, W., Liu, Y., Chen, J., Liu, H., Li, L., Wu, Z., Dong, Y., Li, Y., Qiu, T., He, Y., Lu, Y., Wu, Y., Jiang, Z., Liu, S., ... Busch, C. (2023). NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report. In Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023 (pp. 1808-1825). (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2023-June). IEEE Computer Society. https://doi.org/10.1109/CVPRW59228.2023.00180

@inproceedings{80b07e9357624d4ea45ddc3fc985c2a1,

title = "NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report",

abstract = "This study assesses the outcomes of the NTIRE 2023 Challenge on Non-Homogeneous Dehazing, wherein novel techniques were proposed and evaluated on new image dataset called HD-NH-HAZE. The HD-NH-HAZE dataset contains 50 high resolution pairs of real-life outdoor images featuring nonhomogeneous hazy images and corresponding haze-free images of the same scene. The nonhomogeneous haze was simulated using a professional setup that replicated real-world conditions of hazy scenarios. The competition had 246 participants and 17 teams submitted solutions for the final testing phase. The proposed solutions demonstrated the cutting-edge in image dehazing technology.",

author = "Ancuti, \{Codruta O.\} and Cosmin Ancuti and Vasluianu, \{Florin Alexandru\} and Radu Timofte and Han Zhou and Wei Dong and Yangyi Liu and Jun Chen and Huan Liu and Liangyan Li and Zijun Wu and Yubo Dong and Yuyan Li and Tian Qiu and Yu He and Yonghong Lu and Yinwei Wu and Zhenxiang Jiang and Songhua Liu and Xingyi Yang and Yongcheng Jing and Bilel Benjdira and Ali, \{Anas M.\} and Anis Koubaa and Yang, \{Hao Hsiang\} and Chen, \{I. Hsiang\} and Chen, \{Wei Ting\} and Huang, \{Zhi Kai\} and Chen, \{Yi Chung\} and Hsieh, \{Chia Hsuan\} and Chang, \{Hua En\} and Chiang, \{Yuan Chun\} and Kuo, \{Sy Yen\} and Yu Guo and Yuan Gao and Liu, \{Ryan Wen\} and Yuxu Lu and Jingxiang Qu and Shengfeng He and Wenqi Ren and Trung Hoang and Haichuan Zhang and Amirsaeed Yazdani and Vishal Monga and Lehan Yang and Wu, \{Alex Jiahao\} and Tiancheng Mai and Xiaofeng Cong and Xuemeng Yin and Xuefei Yin and Hazim Emad and Ahmed Abdallah and Yahya Yasser and Dalia Elshahat and Esraa Elbaz and Zhan Li and Wenqing Kuang and Ziwei Luo and Gustafsson, \{Fredrik K.\} and Zheng Zhao and Jens Sj{\"o}lund and Sch{\"o}n, \{Thomas B.\} and Zhao Zhang and Yanyan Wei and Junhu Wang and Suiyi Zhao and Huan Zheng and Jin Guo and Yangfan Sun and Tianli Liu and Dejun Hao and Kui Jiang and Anjali Sarvaiya and Kalpesh Prajapati and Ratnadeep Patra and Pragnesh Barik and Chaitanya Rathod and Kishor Upla and Kiran Raja and Raghavendra Ramachandra and Christoph Busch",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023 ; Conference date: 18-06-2023 Through 22-06-2023",

year = "2023",

doi = "10.1109/CVPRW59228.2023.00180",

language = "英语",

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

publisher = "IEEE Computer Society",

pages = "1808--1825",

booktitle = "Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023",

address = "美国",

}

Ancuti, CO, Ancuti, C, Vasluianu, FA, Timofte, R, Zhou, H, Dong, W, Liu, Y, Chen, J, Liu, H, Li, L, Wu, Z, Dong, Y, Li, Y, Qiu, T, He, Y, Lu, Y, Wu, Y, Jiang, Z, Liu, S, Yang, X, Jing, Y, Benjdira, B, Ali, AM, Koubaa, A, Yang, HH, Chen, IH, Chen, WT, Huang, ZK, Chen, YC, Hsieh, CH, Chang, HE, Chiang, YC, Kuo, SY, Guo, Y, Gao, Y, Liu, RW, Lu, Y, Qu, J, He, S, Ren, W, Hoang, T, Zhang, H, Yazdani, A, Monga, V, Yang, L, Wu, AJ, Mai, T, Cong, X, Yin, X, Yin, X, Emad, H, Abdallah, A, Yasser, Y, Elshahat, D, Elbaz, E, Li, Z, Kuang, W, Luo, Z, Gustafsson, FK, Zhao, Z, Sjölund, J, Schön, TB, Zhang, Z, Wei, Y, Wang, J, Zhao, S, Zheng, H, Guo, J, Sun, Y, Liu, T, Hao, D, Jiang, K, Sarvaiya, A, Prajapati, K, Patra, R, Barik, P, Rathod, C, Upla, K, Raja, K, Ramachandra, R & Busch, C 2023, NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report. in Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 2023-June, IEEE Computer Society, pp. 1808-1825, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023, Vancouver, Canada, 18/06/23. https://doi.org/10.1109/CVPRW59228.2023.00180

NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report. / Ancuti, Codruta O.; Ancuti, Cosmin; Vasluianu, Florin Alexandru et al.
Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023. IEEE Computer Society, 2023. p. 1808-1825 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2023-June).

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

TY - GEN

T1 - NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report

AU - Ancuti, Codruta O.

AU - Ancuti, Cosmin

AU - Vasluianu, Florin Alexandru

AU - Timofte, Radu

AU - Zhou, Han

AU - Dong, Wei

AU - Liu, Yangyi

AU - Chen, Jun

AU - Liu, Huan

AU - Li, Liangyan

AU - Wu, Zijun

AU - Dong, Yubo

AU - Li, Yuyan

AU - Qiu, Tian

AU - He, Yu

AU - Lu, Yonghong

AU - Wu, Yinwei

AU - Jiang, Zhenxiang

AU - Liu, Songhua

AU - Yang, Xingyi

AU - Jing, Yongcheng

AU - Benjdira, Bilel

AU - Ali, Anas M.

AU - Koubaa, Anis

AU - Yang, Hao Hsiang

AU - Chen, I. Hsiang

AU - Chen, Wei Ting

AU - Huang, Zhi Kai

AU - Chen, Yi Chung

AU - Hsieh, Chia Hsuan

AU - Chang, Hua En

AU - Chiang, Yuan Chun

AU - Kuo, Sy Yen

AU - Guo, Yu

AU - Gao, Yuan

AU - Liu, Ryan Wen

AU - Lu, Yuxu

AU - Qu, Jingxiang

AU - He, Shengfeng

AU - Ren, Wenqi

AU - Hoang, Trung

AU - Zhang, Haichuan

AU - Yazdani, Amirsaeed

AU - Monga, Vishal

AU - Yang, Lehan

AU - Wu, Alex Jiahao

AU - Mai, Tiancheng

AU - Cong, Xiaofeng

AU - Yin, Xuemeng

AU - Yin, Xuefei

AU - Emad, Hazim

AU - Abdallah, Ahmed

AU - Yasser, Yahya

AU - Elshahat, Dalia

AU - Elbaz, Esraa

AU - Li, Zhan

AU - Kuang, Wenqing

AU - Luo, Ziwei

AU - Gustafsson, Fredrik K.

AU - Zhao, Zheng

AU - Sjölund, Jens

AU - Schön, Thomas B.

AU - Zhang, Zhao

AU - Wei, Yanyan

AU - Wang, Junhu

AU - Zhao, Suiyi

AU - Zheng, Huan

AU - Guo, Jin

AU - Sun, Yangfan

AU - Liu, Tianli

AU - Hao, Dejun

AU - Jiang, Kui

AU - Sarvaiya, Anjali

AU - Prajapati, Kalpesh

AU - Patra, Ratnadeep

AU - Barik, Pragnesh

AU - Rathod, Chaitanya

AU - Upla, Kishor

AU - Raja, Kiran

AU - Ramachandra, Raghavendra

AU - Busch, Christoph

PY - 2023

Y1 - 2023

N2 - This study assesses the outcomes of the NTIRE 2023 Challenge on Non-Homogeneous Dehazing, wherein novel techniques were proposed and evaluated on new image dataset called HD-NH-HAZE. The HD-NH-HAZE dataset contains 50 high resolution pairs of real-life outdoor images featuring nonhomogeneous hazy images and corresponding haze-free images of the same scene. The nonhomogeneous haze was simulated using a professional setup that replicated real-world conditions of hazy scenarios. The competition had 246 participants and 17 teams submitted solutions for the final testing phase. The proposed solutions demonstrated the cutting-edge in image dehazing technology.

AB - This study assesses the outcomes of the NTIRE 2023 Challenge on Non-Homogeneous Dehazing, wherein novel techniques were proposed and evaluated on new image dataset called HD-NH-HAZE. The HD-NH-HAZE dataset contains 50 high resolution pairs of real-life outdoor images featuring nonhomogeneous hazy images and corresponding haze-free images of the same scene. The nonhomogeneous haze was simulated using a professional setup that replicated real-world conditions of hazy scenarios. The competition had 246 participants and 17 teams submitted solutions for the final testing phase. The proposed solutions demonstrated the cutting-edge in image dehazing technology.

UR - https://www.scopus.com/pages/publications/85170828355

U2 - 10.1109/CVPRW59228.2023.00180

DO - 10.1109/CVPRW59228.2023.00180

M3 - 会议稿件

AN - SCOPUS:85170828355

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

SP - 1808

EP - 1825

BT - Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023

PB - IEEE Computer Society

T2 - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023

Y2 - 18 June 2023 through 22 June 2023

ER -

Ancuti CO, Ancuti C, Vasluianu FA, Timofte R, Zhou H, Dong W et al. NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report. In Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023. IEEE Computer Society. 2023. p. 1808-1825. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). doi: 10.1109/CVPRW59228.2023.00180

NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report

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Bibliographical note

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