NTIRE 2024 Challenge on Bracketing Image Restoration and Enhancement: Datasets, Methods and Results

Zhilu Zhang; Shuohao Zhang; Renlong Wu; Wangmeng Zuo; Radu Timofte; Xiaoxia Xing; Hyunhee Park; Sejun Song; Changho Kim; Xiangyu Kong; Jinlong Wu; Jianxing Zhang; Jingfan Tan; Zikun Liu; Wenhan Luo; Wenjie Lin; Chengzhi Jiang; Mingyan Han; Zhen Liu; Ting Jiang; Jinting Luo; Shen Cheng; Linze Li; Xinhan Niu; Shuaicheng Liu; Kexin Dai; Kangzhen Yang; Tao Hu; Xiangyu Chen; Yu Cao; Qingsen Yan; Yanning Zhang; Genggeng Chen; Yongqing Yang; Wei Dong; Xinwei Dai; Yuanbo Zhou; Xintao Qiu; Hui Tang; Wei Deng; Qingquan Gao; Tong Tong; Peng Zhang; Yifei Chen; Wenbo Xiong; Zhijun Song; Pu Cheng; Taolue Feng; Yunqing He; Daiguo Zhou; Ying Huang; Xiaowen Ma; Peng Wu

doi:10.1109/CVPRW63382.2024.00620

NTIRE 2024 Challenge on Bracketing Image Restoration and Enhancement: Datasets, Methods and Results

Zhilu Zhang
, Shuohao Zhang
, Renlong Wu
, Wangmeng Zuo
, Radu Timofte
, Xiaoxia Xing
, Hyunhee Park
, Sejun Song
, Changho Kim
, Xiangyu Kong
, Jinlong Wu
, Jianxing Zhang
, Jingfan Tan
, Zikun Liu
, Wenhan Luo
, Wenjie Lin
, Chengzhi Jiang
, Mingyan Han
, Zhen Liu
, Ting Jiang

Jinting Luo, Shen Cheng, Linze Li, Xinhan Niu, Shuaicheng Liu, Kexin Dai, Kangzhen Yang, Tao Hu, Xiangyu Chen, Yu Cao, Qingsen Yan, Yanning Zhang, Genggeng Chen, Yongqing Yang, Wei Dong, Xinwei Dai, Yuanbo Zhou, Xintao Qiu, Hui Tang, Wei Deng, Qingquan Gao, Tong Tong, Peng Zhang, Yifei Chen, Wenbo Xiong, Zhijun Song, Pu Cheng, Taolue Feng, Yunqing He, Daiguo Zhou, Ying Huang, Xiaowen Ma, Peng Wu

School of Computer Science

Harbin Institute of Technology
University of Würzburg
Swiss Federal Institute of Technology Zurich

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

37 Scopus citations

Abstract

Low-light photography presents significant challenges. Multi-image processing methods have made numerous attempts to obtain high-quality photos, yet remain unsatisfactory. Recently, bracketing image restoration and enhancement has received increased attention. By leveraging the full potential of multi-exposure images, several tasks (including denoising, deblurring, high dynamic range enhancement, and super-resolution) can be jointly addressed. This paper reviews the NTIRE 2024 challenge on bracketing image restoration and enhancement. In the challenge, participants are required to process multi-exposure RAW images to generate noise-free, blur-free, high dynamic range, and even higher-resolution RAW images. The challenge comprises two tracks. Track 1 does not incorporate the super-resolution task, whereas Track 2 does. Each track featured five teams participating in the final testing phase. The proposed methods establish new state-of-the-art performance benchmarks.

Original language	English
Title of host publication	Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024
Publisher	IEEE Computer Society
Pages	6153-6166
Number of pages	14
ISBN (Electronic)	9798350365474
DOIs	https://doi.org/10.1109/CVPRW63382.2024.00620
State	Published - 2024
Event	2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024 - Seattle, United States Duration: 16 Jun 2024 → 22 Jun 2024

Publication series

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

Conference

Conference	2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024
Country/Territory	United States
City	Seattle
Period	16/06/24 → 22/06/24

Keywords

Challenge
Exposure Bracketing
Image Restoration and Enhancement

Access to Document

10.1109/CVPRW63382.2024.00620

Cite this

Zhang, Z., Zhang, S., Wu, R., Zuo, W., Timofte, R., Xing, X., Park, H., Song, S., Kim, C., Kong, X., Wu, J., Zhang, J., Tan, J., Liu, Z., Luo, W., Lin, W., Jiang, C., Han, M., Liu, Z., ... Wu, P. (2024). NTIRE 2024 Challenge on Bracketing Image Restoration and Enhancement: Datasets, Methods and Results. In Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024 (pp. 6153-6166). (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). IEEE Computer Society. https://doi.org/10.1109/CVPRW63382.2024.00620

Zhang, Zhilu ; Zhang, Shuohao ; Wu, Renlong et al. / NTIRE 2024 Challenge on Bracketing Image Restoration and Enhancement : Datasets, Methods and Results. Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024. IEEE Computer Society, 2024. pp. 6153-6166 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops).

@inproceedings{2bdb708346be4e4aa12ac68795c1af82,

title = "NTIRE 2024 Challenge on Bracketing Image Restoration and Enhancement: Datasets, Methods and Results",

abstract = "Low-light photography presents significant challenges. Multi-image processing methods have made numerous attempts to obtain high-quality photos, yet remain unsatisfactory. Recently, bracketing image restoration and enhancement has received increased attention. By leveraging the full potential of multi-exposure images, several tasks (including denoising, deblurring, high dynamic range enhancement, and super-resolution) can be jointly addressed. This paper reviews the NTIRE 2024 challenge on bracketing image restoration and enhancement. In the challenge, participants are required to process multi-exposure RAW images to generate noise-free, blur-free, high dynamic range, and even higher-resolution RAW images. The challenge comprises two tracks. Track 1 does not incorporate the super-resolution task, whereas Track 2 does. Each track featured five teams participating in the final testing phase. The proposed methods establish new state-of-the-art performance benchmarks.",

keywords = "Challenge, Exposure Bracketing, Image Restoration and Enhancement",

author = "Zhilu Zhang and Shuohao Zhang and Renlong Wu and Wangmeng Zuo and Radu Timofte and Xiaoxia Xing and Hyunhee Park and Sejun Song and Changho Kim and Xiangyu Kong and Jinlong Wu and Jianxing Zhang and Jingfan Tan and Zikun Liu and Wenhan Luo and Wenjie Lin and Chengzhi Jiang and Mingyan Han and Zhen Liu and Ting Jiang and Jinting Luo and Shen Cheng and Linze Li and Xinhan Niu and Shuaicheng Liu and Kexin Dai and Kangzhen Yang and Tao Hu and Xiangyu Chen and Yu Cao and Qingsen Yan and Yanning Zhang and Genggeng Chen and Yongqing Yang and Wei Dong and Xinwei Dai and Yuanbo Zhou and Xintao Qiu and Hui Tang and Wei Deng and Qingquan Gao and Tong Tong and Peng Zhang and Yifei Chen and Wenbo Xiong and Zhijun Song and Pu Cheng and Taolue Feng and Yunqing He and Daiguo Zhou and Ying Huang and Xiaowen Ma and Peng Wu",

note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024 ; Conference date: 16-06-2024 Through 22-06-2024",

year = "2024",

doi = "10.1109/CVPRW63382.2024.00620",

language = "英语",

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

publisher = "IEEE Computer Society",

pages = "6153--6166",

booktitle = "Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024",

}

Zhang, Z, Zhang, S, Wu, R, Zuo, W, Timofte, R, Xing, X, Park, H, Song, S, Kim, C, Kong, X, Wu, J, Zhang, J, Tan, J, Liu, Z, Luo, W, Lin, W, Jiang, C, Han, M, Liu, Z, Jiang, T, Luo, J, Cheng, S, Li, L, Niu, X, Liu, S, Dai, K, Yang, K, Hu, T, Chen, X, Cao, Y, Yan, Q , Zhang, Y, Chen, G, Yang, Y, Dong, W, Dai, X, Zhou, Y, Qiu, X, Tang, H, Deng, W, Gao, Q, Tong, T, Zhang, P, Chen, Y, Xiong, W, Song, Z, Cheng, P, Feng, T, He, Y, Zhou, D, Huang, Y, Ma, X & Wu, P 2024, NTIRE 2024 Challenge on Bracketing Image Restoration and Enhancement: Datasets, Methods and Results. in Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, IEEE Computer Society, pp. 6153-6166, 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024, Seattle, United States, 16/06/24. https://doi.org/10.1109/CVPRW63382.2024.00620

NTIRE 2024 Challenge on Bracketing Image Restoration and Enhancement: Datasets, Methods and Results. / Zhang, Zhilu; Zhang, Shuohao; Wu, Renlong et al.
Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024. IEEE Computer Society, 2024. p. 6153-6166 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops).

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

TY - GEN

T1 - NTIRE 2024 Challenge on Bracketing Image Restoration and Enhancement

T2 - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024

AU - Zhang, Zhilu

AU - Zhang, Shuohao

AU - Wu, Renlong

AU - Zuo, Wangmeng

AU - Timofte, Radu

AU - Xing, Xiaoxia

AU - Park, Hyunhee

AU - Song, Sejun

AU - Kim, Changho

AU - Kong, Xiangyu

AU - Wu, Jinlong

AU - Zhang, Jianxing

AU - Tan, Jingfan

AU - Liu, Zikun

AU - Luo, Wenhan

AU - Lin, Wenjie

AU - Jiang, Chengzhi

AU - Han, Mingyan

AU - Liu, Zhen

AU - Jiang, Ting

AU - Luo, Jinting

AU - Cheng, Shen

AU - Li, Linze

AU - Niu, Xinhan

AU - Liu, Shuaicheng

AU - Dai, Kexin

AU - Yang, Kangzhen

AU - Hu, Tao

AU - Chen, Xiangyu

AU - Cao, Yu

AU - Yan, Qingsen

AU - Zhang, Yanning

AU - Chen, Genggeng

AU - Yang, Yongqing

AU - Dong, Wei

AU - Dai, Xinwei

AU - Zhou, Yuanbo

AU - Qiu, Xintao

AU - Tang, Hui

AU - Deng, Wei

AU - Gao, Qingquan

AU - Tong, Tong

AU - Zhang, Peng

AU - Chen, Yifei

AU - Xiong, Wenbo

AU - Song, Zhijun

AU - Cheng, Pu

AU - Feng, Taolue

AU - He, Yunqing

AU - Zhou, Daiguo

AU - Huang, Ying

AU - Ma, Xiaowen

AU - Wu, Peng

PY - 2024

Y1 - 2024

N2 - Low-light photography presents significant challenges. Multi-image processing methods have made numerous attempts to obtain high-quality photos, yet remain unsatisfactory. Recently, bracketing image restoration and enhancement has received increased attention. By leveraging the full potential of multi-exposure images, several tasks (including denoising, deblurring, high dynamic range enhancement, and super-resolution) can be jointly addressed. This paper reviews the NTIRE 2024 challenge on bracketing image restoration and enhancement. In the challenge, participants are required to process multi-exposure RAW images to generate noise-free, blur-free, high dynamic range, and even higher-resolution RAW images. The challenge comprises two tracks. Track 1 does not incorporate the super-resolution task, whereas Track 2 does. Each track featured five teams participating in the final testing phase. The proposed methods establish new state-of-the-art performance benchmarks.

AB - Low-light photography presents significant challenges. Multi-image processing methods have made numerous attempts to obtain high-quality photos, yet remain unsatisfactory. Recently, bracketing image restoration and enhancement has received increased attention. By leveraging the full potential of multi-exposure images, several tasks (including denoising, deblurring, high dynamic range enhancement, and super-resolution) can be jointly addressed. This paper reviews the NTIRE 2024 challenge on bracketing image restoration and enhancement. In the challenge, participants are required to process multi-exposure RAW images to generate noise-free, blur-free, high dynamic range, and even higher-resolution RAW images. The challenge comprises two tracks. Track 1 does not incorporate the super-resolution task, whereas Track 2 does. Each track featured five teams participating in the final testing phase. The proposed methods establish new state-of-the-art performance benchmarks.

KW - Challenge

KW - Exposure Bracketing

KW - Image Restoration and Enhancement

UR - https://www.scopus.com/pages/publications/85191710437

U2 - 10.1109/CVPRW63382.2024.00620

DO - 10.1109/CVPRW63382.2024.00620

M3 - 会议稿件

AN - SCOPUS:85191710437

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

SP - 6153

EP - 6166

BT - Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024

PB - IEEE Computer Society

Y2 - 16 June 2024 through 22 June 2024

ER -

Zhang Z, Zhang S, Wu R, Zuo W, Timofte R, Xing X et al. NTIRE 2024 Challenge on Bracketing Image Restoration and Enhancement: Datasets, Methods and Results. In Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024. IEEE Computer Society. 2024. p. 6153-6166. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). doi: 10.1109/CVPRW63382.2024.00620

NTIRE 2024 Challenge on Bracketing Image Restoration and Enhancement: Datasets, Methods and Results

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