NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results

Eduardo Perez-Pellitero; Sibi Catley-Chandar; Richard Shaw; Ales Leonardis; Radu Timofte; Zexin Zhang; Cen Liu; Yunbo Peng; Yue Lin; Gaocheng Yu; Jin Zhang; Zhe Ma; Hongbin Wang; Xiangyu Chen; Xintao Wang; Haiwei Wu; Lin Liu; Chao Dong; Jiantao Zhou; Qingsen Yan; Song Zhang; Weiye Chen; Yuhang Liu; Zhen Zhang; Yanning Zhang; Javen Qinfeng Shi; Dong Gong; Dan Zhu; Mengdi Sun; Guannan Chen; Yang Hu; Haowei Li; Baozhu Zou; Zhen Liu; Wenjie Lin; Ting Jiang; Chengzhi Jiang; Xinpeng Li; Mingyan Han; Haoqiang Fan; Jian Sun; Shuaicheng Liu; Juan Marin-Vega; Michael Sloth; Peter Schneider-Kamp; Richard Rottger; Chunyang Li; Long Bao; Gang He; Ziyao Xu; Li Xu; Gen Zhan; Ming Sun; Xing Wen; Junlin Li; Jinjing Li; Chenghua Li; Ruipeng Gang; Fangya Li; Chenming Liu; Shuang Feng; Fei Lei; Rui Liu; Junxiang Ruan; Tianhong Dai; Wei Li; Zhan Lu; Hengyan Liu; Peian Huang; Guangyu Ren; Yonglin Luo; Chang Liu; Qiang Tu; Fangya Li; Ruipeng Gang; Chenghua Li; Jinjing Li; Sai Ma; Chenming Liu; Yizhen Cao; Steven Tel; Barthelemy Heyrman; Dominique Ginhac; Chul Lee; Gahyeon Kim; Seonghyun Park; An Gia Vien; Truong Thanh Nhat Mai; Howoon Yoon; Tu Vo; Alexander Holston; Sheir Zaheer; Chan Y. Park

doi:10.1109/CVPRW56347.2022.00114

NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results

Eduardo Perez-Pellitero^*, Sibi Catley-Chandar, Richard Shaw, Ales Leonardis, Radu Timofte, Zexin Zhang, Cen Liu, Yunbo Peng, Yue Lin, Gaocheng Yu, Jin Zhang, Zhe Ma, Hongbin Wang, Xiangyu Chen, Xintao Wang, Haiwei Wu, Lin Liu, Chao Dong, Jiantao Zhou, Qingsen YanSong Zhang, Weiye Chen, Yuhang Liu, Zhen Zhang, Yanning Zhang, Javen Qinfeng Shi, Dong Gong, Dan Zhu, Mengdi Sun, Guannan Chen, Yang Hu, Haowei Li, Baozhu Zou, Zhen Liu, Wenjie Lin, Ting Jiang, Chengzhi Jiang, Xinpeng Li, Mingyan Han, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Juan Marin-Vega, Michael Sloth, Peter Schneider-Kamp, Richard Rottger, Chunyang Li, Long Bao, Gang He, Ziyao Xu, Li Xu, Gen Zhan, Ming Sun, Xing Wen, Junlin Li, Jinjing Li, Chenghua Li, Ruipeng Gang, Fangya Li, Chenming Liu, Shuang Feng, Fei Lei, Rui Liu, Junxiang Ruan, Tianhong Dai, Wei Li, Zhan Lu, Hengyan Liu, Peian Huang, Guangyu Ren, Yonglin Luo, Chang Liu, Qiang Tu, Fangya Li, Ruipeng Gang, Chenghua Li, Jinjing Li, Sai Ma, Chenming Liu, Yizhen Cao, Steven Tel, Barthelemy Heyrman, Dominique Ginhac, Chul Lee, Gahyeon Kim, Seonghyun Park, An Gia Vien, Truong Thanh Nhat Mai, Howoon Yoon, Tu Vo, Alexander Holston, Sheir Zaheer, Chan Y. Park

^*Corresponding author for this work

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

29 Citations (Scopus)

Abstract

This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022. This manuscript focuses on the competition set-up, datasets, the proposed methods and their results. The challenge aims at estimating an HDR image from multiple respective low dynamic range (LDR) observations, which might suffer from under-or over-exposed regions and different sources of noise. The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i.e. solutions can not exceed a given number of operations). In Track 2, participants are asked to minimize the complexity of their solutions while imposing a constraint on fidelity scores (i.e. solutions are required to obtain a higher fidelity score than the prescribed baseline). Both tracks use the same data and metrics: Fidelity is measured by means of PSNR with respect to a ground-truth HDR image (computed both directly and with a canonical tonemapping operation), while complexity metrics include the number of Multiply-Accumulate (MAC) operations and runtime (in seconds).

Original language	English
Title of host publication	Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
Publisher	IEEE Computer Society
Pages	1008-1022
Number of pages	15
ISBN (Electronic)	9781665487399
DOIs	https://doi.org/10.1109/CVPRW56347.2022.00114
Publication status	Published - 2022
Externally published	Yes
Event	2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 - New Orleans, United States Duration: 19 Jun 2022 → 20 Jun 2022

Publication series

Name	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume	2022-June
ISSN (Print)	2160-7508
ISSN (Electronic)	2160-7516

Conference

Conference	2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
Country/Territory	United States
City	New Orleans
Period	19/06/22 → 20/06/22

Access to Document

10.1109/CVPRW56347.2022.00114

Cite this

Perez-Pellitero, E., Catley-Chandar, S., Shaw, R., Leonardis, A., Timofte, R., Zhang, Z., Liu, C., Peng, Y., Lin, Y., Yu, G., Zhang, J., Ma, Z., Wang, H., Chen, X., Wang, X., Wu, H., Liu, L., Dong, C., Zhou, J., ... Park, C. Y. (2022). NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results. In Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 (pp. 1008-1022). (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2022-June). IEEE Computer Society. https://doi.org/10.1109/CVPRW56347.2022.00114

Perez-Pellitero, Eduardo ; Catley-Chandar, Sibi ; Shaw, Richard et al. / NTIRE 2022 Challenge on High Dynamic Range Imaging : Methods and Results. Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. IEEE Computer Society, 2022. pp. 1008-1022 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops).

@inproceedings{069e5450ad604e25965969bd6c8d34b0,

title = "NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results",

abstract = "This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022. This manuscript focuses on the competition set-up, datasets, the proposed methods and their results. The challenge aims at estimating an HDR image from multiple respective low dynamic range (LDR) observations, which might suffer from under-or over-exposed regions and different sources of noise. The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i.e. solutions can not exceed a given number of operations). In Track 2, participants are asked to minimize the complexity of their solutions while imposing a constraint on fidelity scores (i.e. solutions are required to obtain a higher fidelity score than the prescribed baseline). Both tracks use the same data and metrics: Fidelity is measured by means of PSNR with respect to a ground-truth HDR image (computed both directly and with a canonical tonemapping operation), while complexity metrics include the number of Multiply-Accumulate (MAC) operations and runtime (in seconds).",

author = "Eduardo Perez-Pellitero and Sibi Catley-Chandar and Richard Shaw and Ales Leonardis and Radu Timofte and Zexin Zhang and Cen Liu and Yunbo Peng and Yue Lin and Gaocheng Yu and Jin Zhang and Zhe Ma and Hongbin Wang and Xiangyu Chen and Xintao Wang and Haiwei Wu and Lin Liu and Chao Dong and Jiantao Zhou and Qingsen Yan and Song Zhang and Weiye Chen and Yuhang Liu and Zhen Zhang and Yanning Zhang and Shi, {Javen Qinfeng} and Dong Gong and Dan Zhu and Mengdi Sun and Guannan Chen and Yang Hu and Haowei Li and Baozhu Zou and Zhen Liu and Wenjie Lin and Ting Jiang and Chengzhi Jiang and Xinpeng Li and Mingyan Han and Haoqiang Fan and Jian Sun and Shuaicheng Liu and Juan Marin-Vega and Michael Sloth and Peter Schneider-Kamp and Richard Rottger and Chunyang Li and Long Bao and Gang He and Ziyao Xu and Li Xu and Gen Zhan and Ming Sun and Xing Wen and Junlin Li and Jinjing Li and Chenghua Li and Ruipeng Gang and Fangya Li and Chenming Liu and Shuang Feng and Fei Lei and Rui Liu and Junxiang Ruan and Tianhong Dai and Wei Li and Zhan Lu and Hengyan Liu and Peian Huang and Guangyu Ren and Yonglin Luo and Chang Liu and Qiang Tu and Fangya Li and Ruipeng Gang and Chenghua Li and Jinjing Li and Sai Ma and Chenming Liu and Yizhen Cao and Steven Tel and Barthelemy Heyrman and Dominique Ginhac and Chul Lee and Gahyeon Kim and Seonghyun Park and Vien, {An Gia} and {Thanh Nhat Mai}, Truong and Howoon Yoon and Tu Vo and Alexander Holston and Sheir Zaheer and Park, {Chan Y.}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 ; Conference date: 19-06-2022 Through 20-06-2022",

year = "2022",

doi = "10.1109/CVPRW56347.2022.00114",

language = "English",

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

publisher = "IEEE Computer Society",

pages = "1008--1022",

booktitle = "Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022",

}

Perez-Pellitero, E, Catley-Chandar, S, Shaw, R, Leonardis, A, Timofte, R, Zhang, Z, Liu, C, Peng, Y, Lin, Y, Yu, G, Zhang, J, Ma, Z, Wang, H, Chen, X, Wang, X, Wu, H, Liu, L, Dong, C, Zhou, J, Yan, Q, Zhang, S, Chen, W, Liu, Y, Zhang, Z, Zhang, Y, Shi, JQ, Gong, D, Zhu, D, Sun, M, Chen, G, Hu, Y, Li, H, Zou, B, Liu, Z, Lin, W, Jiang, T, Jiang, C, Li, X, Han, M, Fan, H, Sun, J, Liu, S, Marin-Vega, J, Sloth, M, Schneider-Kamp, P, Rottger, R, Li, C, Bao, L, He, G, Xu, Z, Xu, L, Zhan, G, Sun, M, Wen, X, Li, J, Li, J, Li, C, Gang, R, Li, F, Liu, C, Feng, S, Lei, F, Liu, R, Ruan, J, Dai, T, Li, W, Lu, Z, Liu, H, Huang, P, Ren, G, Luo, Y, Liu, C, Tu, Q, Li, F, Gang, R, Li, C, Li, J, Ma, S, Liu, C, Cao, Y, Tel, S, Heyrman, B, Ginhac, D, Lee, C, Kim, G, Park, S, Vien, AG, Thanh Nhat Mai, T, Yoon, H, Vo, T, Holston, A, Zaheer, S & Park, CY 2022, NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results. in Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 2022-June, IEEE Computer Society, pp. 1008-1022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022, New Orleans, United States, 19/06/22. https://doi.org/10.1109/CVPRW56347.2022.00114

NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results. / Perez-Pellitero, Eduardo; Catley-Chandar, Sibi; Shaw, Richard et al.
Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. IEEE Computer Society, 2022. p. 1008-1022 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2022-June).

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

TY - GEN

T1 - NTIRE 2022 Challenge on High Dynamic Range Imaging

T2 - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022

AU - Perez-Pellitero, Eduardo

AU - Catley-Chandar, Sibi

AU - Shaw, Richard

AU - Leonardis, Ales

AU - Timofte, Radu

AU - Zhang, Zexin

AU - Liu, Cen

AU - Peng, Yunbo

AU - Lin, Yue

AU - Yu, Gaocheng

AU - Zhang, Jin

AU - Ma, Zhe

AU - Wang, Hongbin

AU - Chen, Xiangyu

AU - Wang, Xintao

AU - Wu, Haiwei

AU - Liu, Lin

AU - Dong, Chao

AU - Zhou, Jiantao

AU - Yan, Qingsen

AU - Zhang, Song

AU - Chen, Weiye

AU - Liu, Yuhang

AU - Zhang, Zhen

AU - Zhang, Yanning

AU - Shi, Javen Qinfeng

AU - Gong, Dong

AU - Zhu, Dan

AU - Sun, Mengdi

AU - Chen, Guannan

AU - Hu, Yang

AU - Li, Haowei

AU - Zou, Baozhu

AU - Liu, Zhen

AU - Lin, Wenjie

AU - Jiang, Ting

AU - Jiang, Chengzhi

AU - Li, Xinpeng

AU - Han, Mingyan

AU - Fan, Haoqiang

AU - Sun, Jian

AU - Liu, Shuaicheng

AU - Marin-Vega, Juan

AU - Sloth, Michael

AU - Schneider-Kamp, Peter

AU - Rottger, Richard

AU - Li, Chunyang

AU - Bao, Long

AU - He, Gang

AU - Xu, Ziyao

AU - Xu, Li

AU - Zhan, Gen

AU - Sun, Ming

AU - Wen, Xing

AU - Li, Junlin

AU - Li, Jinjing

AU - Li, Chenghua

AU - Gang, Ruipeng

AU - Li, Fangya

AU - Liu, Chenming

AU - Feng, Shuang

AU - Lei, Fei

AU - Liu, Rui

AU - Ruan, Junxiang

AU - Dai, Tianhong

AU - Li, Wei

AU - Lu, Zhan

AU - Liu, Hengyan

AU - Huang, Peian

AU - Ren, Guangyu

AU - Luo, Yonglin

AU - Liu, Chang

AU - Tu, Qiang

AU - Li, Fangya

AU - Gang, Ruipeng

AU - Li, Chenghua

AU - Li, Jinjing

AU - Ma, Sai

AU - Liu, Chenming

AU - Cao, Yizhen

AU - Tel, Steven

AU - Heyrman, Barthelemy

AU - Ginhac, Dominique

AU - Lee, Chul

AU - Kim, Gahyeon

AU - Park, Seonghyun

AU - Vien, An Gia

AU - Thanh Nhat Mai, Truong

AU - Yoon, Howoon

AU - Vo, Tu

AU - Holston, Alexander

AU - Zaheer, Sheir

AU - Park, Chan Y.

PY - 2022

Y1 - 2022

N2 - This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022. This manuscript focuses on the competition set-up, datasets, the proposed methods and their results. The challenge aims at estimating an HDR image from multiple respective low dynamic range (LDR) observations, which might suffer from under-or over-exposed regions and different sources of noise. The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i.e. solutions can not exceed a given number of operations). In Track 2, participants are asked to minimize the complexity of their solutions while imposing a constraint on fidelity scores (i.e. solutions are required to obtain a higher fidelity score than the prescribed baseline). Both tracks use the same data and metrics: Fidelity is measured by means of PSNR with respect to a ground-truth HDR image (computed both directly and with a canonical tonemapping operation), while complexity metrics include the number of Multiply-Accumulate (MAC) operations and runtime (in seconds).

AB - This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022. This manuscript focuses on the competition set-up, datasets, the proposed methods and their results. The challenge aims at estimating an HDR image from multiple respective low dynamic range (LDR) observations, which might suffer from under-or over-exposed regions and different sources of noise. The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i.e. solutions can not exceed a given number of operations). In Track 2, participants are asked to minimize the complexity of their solutions while imposing a constraint on fidelity scores (i.e. solutions are required to obtain a higher fidelity score than the prescribed baseline). Both tracks use the same data and metrics: Fidelity is measured by means of PSNR with respect to a ground-truth HDR image (computed both directly and with a canonical tonemapping operation), while complexity metrics include the number of Multiply-Accumulate (MAC) operations and runtime (in seconds).

UR - http://www.scopus.com/inward/record.url?scp=85129495382&partnerID=8YFLogxK

U2 - 10.1109/CVPRW56347.2022.00114

DO - 10.1109/CVPRW56347.2022.00114

M3 - Conference Proceeding

AN - SCOPUS:85129495382

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

SP - 1008

EP - 1022

BT - Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022

PB - IEEE Computer Society

Y2 - 19 June 2022 through 20 June 2022

ER -

Perez-Pellitero E, Catley-Chandar S, Shaw R, Leonardis A, Timofte R, Zhang Z et al. NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results. In Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. IEEE Computer Society. 2022. p. 1008-1022. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). doi: 10.1109/CVPRW56347.2022.00114

NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results

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