AIM 2020: Scene Relighting and Illumination Estimation Challenge

Majed El Helou; Ruofan Zhou; Sabine Süsstrunk; Radu Timofte; Mahmoud Afifi; Michael S. Brown; Kele Xu; Hengxing Cai; Yuzhong Liu; Li Wen Wang; Zhi Song Liu; Chu Tak Li; Sourya Dipta Das; Nisarg A. Shah; Akashdeep Jassal; Tongtong Zhao; Shanshan Zhao; Sabari Nathan; M. Parisa Beham; R. Suganya; Qing Wang; Zhongyun Hu; Xin Huang; Yaning Li; Maitreya Suin; Kuldeep Purohit; A. N. Rajagopalan; Densen Puthussery; P. S. Hrishikesh; Melvin Kuriakose; C. V. Jiji; Yu Zhu; Liping Dong; Zhuolong Jiang; Chenghua Li; Cong Leng; Jian Cheng

doi:10.1007/978-3-030-67070-2_30

AIM 2020: Scene Relighting and Illumination Estimation Challenge

Majed El Helou
, Ruofan Zhou
, Sabine Süsstrunk
, Radu Timofte
, Mahmoud Afifi
, Michael S. Brown
, Kele Xu
, Hengxing Cai
, Yuzhong Liu
, Li Wen Wang
, Zhi Song Liu
, Chu Tak Li
, Sourya Dipta Das
, Nisarg A. Shah
, Akashdeep Jassal
, Tongtong Zhao
, Shanshan Zhao
, Sabari Nathan
, M. Parisa Beham
, R. Suganya

Qing Wang, Zhongyun Hu, Xin Huang, Yaning Li, Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan, Densen Puthussery, P. S. Hrishikesh, Melvin Kuriakose, C. V. Jiji, Yu Zhu, Liping Dong, Zhuolong Jiang, Chenghua Li, Cong Leng, Jian Cheng

School of Computer Science

Swiss Federal Institute of Technology Lausanne
Swiss Federal Institute of Technology Zurich
York University Toronto
National University of Defense Technology
Hong Kong Polytechnic University
Institut Polytechnique de Paris
Jadavpur University
Indian Institute of Technology Jodhpur
PEC University of Technology
Dalian Maritime University
China Everbright Bank
Couger Inc.
Sethu Institute of Technology
Thiagarajar College of Engineering
Northwestern Polytechnical University Xian
Indian Institute of Technology Madras
College of Engineering Trivandrum
Chinese Academy of Sciences

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

28 Scopus citations

Abstract

We review the AIM 2020 challenge on virtual image relighting and illumination estimation. This paper presents the novel VIDIT dataset used in the challenge and the different proposed solutions and final evaluation results over the 3 challenge tracks. The first track considered one-to-one relighting; the objective was to relight an input photo of a scene with a different color temperature and illuminant orientation (i.e., light source position). The goal of the second track was to estimate illumination settings, namely the color temperature and orientation, from a given image. Lastly, the third track dealt with any-to-any relighting, thus a generalization of the first track. The target color temperature and orientation, rather than being pre-determined, are instead given by a guide image. Participants were allowed to make use of their track 1 and 2 solutions for track 3. The tracks had 94, 52, and 56 registered participants, respectively, leading to 20 confirmed submissions in the final competition stage.

Original language	English
Title of host publication	Computer Vision – ECCV 2020 Workshops, Proceedings
Editors	Adrien Bartoli, Andrea Fusiello
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	499-518
Number of pages	20
ISBN (Print)	9783030670696
DOIs	https://doi.org/10.1007/978-3-030-67070-2_30
State	Published - 2020
Event	Workshops held at the 16th European Conference on Computer Vision, ECCV 2020 - Glasgow, United Kingdom Duration: 23 Aug 2020 → 28 Aug 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12537 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Workshops held at the 16th European Conference on Computer Vision, ECCV 2020
Country/Territory	United Kingdom
City	Glasgow
Period	23/08/20 → 28/08/20

Keywords

Illumination estimation
Image relighting
Style transfer

Access to Document

10.1007/978-3-030-67070-2_30

Cite this

El Helou, M., Zhou, R., Süsstrunk, S., Timofte, R., Afifi, M., Brown, M. S., Xu, K., Cai, H., Liu, Y., Wang, L. W., Liu, Z. S., Li, C. T., Dipta Das, S., Shah, N. A., Jassal, A., Zhao, T., Zhao, S., Nathan, S., Beham, M. P., ... Cheng, J. (2020). AIM 2020: Scene Relighting and Illumination Estimation Challenge. In A. Bartoli, & A. Fusiello (Eds.), Computer Vision – ECCV 2020 Workshops, Proceedings (pp. 499-518). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12537 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-67070-2_30

El Helou, Majed ; Zhou, Ruofan ; Süsstrunk, Sabine et al. / AIM 2020 : Scene Relighting and Illumination Estimation Challenge. Computer Vision – ECCV 2020 Workshops, Proceedings. editor / Adrien Bartoli ; Andrea Fusiello. Springer Science and Business Media Deutschland GmbH, 2020. pp. 499-518 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{ad1e44436a824588a74d491f4d9ee077,

title = "AIM 2020: Scene Relighting and Illumination Estimation Challenge",

abstract = "We review the AIM 2020 challenge on virtual image relighting and illumination estimation. This paper presents the novel VIDIT dataset used in the challenge and the different proposed solutions and final evaluation results over the 3 challenge tracks. The first track considered one-to-one relighting; the objective was to relight an input photo of a scene with a different color temperature and illuminant orientation (i.e., light source position). The goal of the second track was to estimate illumination settings, namely the color temperature and orientation, from a given image. Lastly, the third track dealt with any-to-any relighting, thus a generalization of the first track. The target color temperature and orientation, rather than being pre-determined, are instead given by a guide image. Participants were allowed to make use of their track 1 and 2 solutions for track 3. The tracks had 94, 52, and 56 registered participants, respectively, leading to 20 confirmed submissions in the final competition stage.",

keywords = "Illumination estimation, Image relighting, Style transfer",

author = "\{El Helou\}, Majed and Ruofan Zhou and Sabine S{\"u}sstrunk and Radu Timofte and Mahmoud Afifi and Brown, \{Michael S.\} and Kele Xu and Hengxing Cai and Yuzhong Liu and Wang, \{Li Wen\} and Liu, \{Zhi Song\} and Li, \{Chu Tak\} and \{Dipta Das\}, Sourya and Shah, \{Nisarg A.\} and Akashdeep Jassal and Tongtong Zhao and Shanshan Zhao and Sabari Nathan and Beham, \{M. Parisa\} and R. Suganya and Qing Wang and Zhongyun Hu and Xin Huang and Yaning Li and Maitreya Suin and Kuldeep Purohit and Rajagopalan, \{A. N.\} and Densen Puthussery and Hrishikesh, \{P. S.\} and Melvin Kuriakose and Jiji, \{C. V.\} and Yu Zhu and Liping Dong and Zhuolong Jiang and Chenghua Li and Cong Leng and Jian Cheng",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; Workshops held at the 16th European Conference on Computer Vision, ECCV 2020 ; Conference date: 23-08-2020 Through 28-08-2020",

year = "2020",

doi = "10.1007/978-3-030-67070-2\_30",

language = "英语",

isbn = "9783030670696",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "499--518",

editor = "Adrien Bartoli and Andrea Fusiello",

booktitle = "Computer Vision – ECCV 2020 Workshops, Proceedings",

}

El Helou, M, Zhou, R, Süsstrunk, S, Timofte, R, Afifi, M, Brown, MS, Xu, K, Cai, H, Liu, Y, Wang, LW, Liu, ZS, Li, CT, Dipta Das, S, Shah, NA, Jassal, A, Zhao, T, Zhao, S, Nathan, S, Beham, MP, Suganya, R, Wang, Q, Hu, Z, Huang, X, Li, Y, Suin, M, Purohit, K, Rajagopalan, AN, Puthussery, D, Hrishikesh, PS, Kuriakose, M, Jiji, CV, Zhu, Y, Dong, L, Jiang, Z, Li, C, Leng, C & Cheng, J 2020, AIM 2020: Scene Relighting and Illumination Estimation Challenge. in A Bartoli & A Fusiello (eds), Computer Vision – ECCV 2020 Workshops, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12537 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 499-518, Workshops held at the 16th European Conference on Computer Vision, ECCV 2020, Glasgow, United Kingdom, 23/08/20. https://doi.org/10.1007/978-3-030-67070-2_30

AIM 2020: Scene Relighting and Illumination Estimation Challenge. / El Helou, Majed; Zhou, Ruofan; Süsstrunk, Sabine et al.
Computer Vision – ECCV 2020 Workshops, Proceedings. ed. / Adrien Bartoli; Andrea Fusiello. Springer Science and Business Media Deutschland GmbH, 2020. p. 499-518 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12537 LNCS).

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

TY - GEN

T1 - AIM 2020

T2 - Workshops held at the 16th European Conference on Computer Vision, ECCV 2020

AU - El Helou, Majed

AU - Zhou, Ruofan

AU - Süsstrunk, Sabine

AU - Timofte, Radu

AU - Afifi, Mahmoud

AU - Brown, Michael S.

AU - Xu, Kele

AU - Cai, Hengxing

AU - Liu, Yuzhong

AU - Wang, Li Wen

AU - Liu, Zhi Song

AU - Li, Chu Tak

AU - Dipta Das, Sourya

AU - Shah, Nisarg A.

AU - Jassal, Akashdeep

AU - Zhao, Tongtong

AU - Zhao, Shanshan

AU - Nathan, Sabari

AU - Beham, M. Parisa

AU - Suganya, R.

AU - Wang, Qing

AU - Hu, Zhongyun

AU - Huang, Xin

AU - Li, Yaning

AU - Suin, Maitreya

AU - Purohit, Kuldeep

AU - Rajagopalan, A. N.

AU - Puthussery, Densen

AU - Hrishikesh, P. S.

AU - Kuriakose, Melvin

AU - Jiji, C. V.

AU - Zhu, Yu

AU - Dong, Liping

AU - Jiang, Zhuolong

AU - Li, Chenghua

AU - Leng, Cong

AU - Cheng, Jian

PY - 2020

Y1 - 2020

N2 - We review the AIM 2020 challenge on virtual image relighting and illumination estimation. This paper presents the novel VIDIT dataset used in the challenge and the different proposed solutions and final evaluation results over the 3 challenge tracks. The first track considered one-to-one relighting; the objective was to relight an input photo of a scene with a different color temperature and illuminant orientation (i.e., light source position). The goal of the second track was to estimate illumination settings, namely the color temperature and orientation, from a given image. Lastly, the third track dealt with any-to-any relighting, thus a generalization of the first track. The target color temperature and orientation, rather than being pre-determined, are instead given by a guide image. Participants were allowed to make use of their track 1 and 2 solutions for track 3. The tracks had 94, 52, and 56 registered participants, respectively, leading to 20 confirmed submissions in the final competition stage.

AB - We review the AIM 2020 challenge on virtual image relighting and illumination estimation. This paper presents the novel VIDIT dataset used in the challenge and the different proposed solutions and final evaluation results over the 3 challenge tracks. The first track considered one-to-one relighting; the objective was to relight an input photo of a scene with a different color temperature and illuminant orientation (i.e., light source position). The goal of the second track was to estimate illumination settings, namely the color temperature and orientation, from a given image. Lastly, the third track dealt with any-to-any relighting, thus a generalization of the first track. The target color temperature and orientation, rather than being pre-determined, are instead given by a guide image. Participants were allowed to make use of their track 1 and 2 solutions for track 3. The tracks had 94, 52, and 56 registered participants, respectively, leading to 20 confirmed submissions in the final competition stage.

KW - Illumination estimation

KW - Image relighting

KW - Style transfer

UR - https://www.scopus.com/pages/publications/85101493640

U2 - 10.1007/978-3-030-67070-2_30

DO - 10.1007/978-3-030-67070-2_30

M3 - 会议稿件

AN - SCOPUS:85101493640

SN - 9783030670696

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 499

EP - 518

BT - Computer Vision – ECCV 2020 Workshops, Proceedings

A2 - Bartoli, Adrien

A2 - Fusiello, Andrea

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 23 August 2020 through 28 August 2020

ER -

El Helou M, Zhou R, Süsstrunk S, Timofte R, Afifi M, Brown MS et al. AIM 2020: Scene Relighting and Illumination Estimation Challenge. In Bartoli A, Fusiello A, editors, Computer Vision – ECCV 2020 Workshops, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 499-518. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-67070-2_30

AIM 2020: Scene Relighting and Illumination Estimation Challenge

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Keywords

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