AIM 2019 challenge on constrained super-resolution: Methods and results

Kai Zhang; Shuhang Gu; Radu Timofte; Zheng Hui; Xiumei Wang; Xinbo Gao; Dongliang Xiong; Shuai Liu; Ruipeng Gang; Nan Nan; Chenghua Li; Xueyi Zou; Ning Kang; Zhan Wang; Hang Xu; Chaofeng Wang; Zheng Li; Linlin Wang; Jun Shi; Wenyu Sun; Zhiqiang Lang; Jiangtao Nie; Wei Wei; Lei Zhang; Yazhe Niu; Peijin Zhuo; Xiangzhen Kong; Long Sun; Wenhao Wang

doi:10.1109/ICCVW.2019.00441

AIM 2019 challenge on constrained super-resolution: Methods and results

Kai Zhang
, Shuhang Gu
, Radu Timofte
, Zheng Hui
, Xiumei Wang
, Xinbo Gao
, Dongliang Xiong
, Shuai Liu
, Ruipeng Gang
, Nan Nan
, Chenghua Li
, Xueyi Zou
, Ning Kang
, Zhan Wang
, Hang Xu
, Chaofeng Wang
, Zheng Li
, Linlin Wang
, Jun Shi
, Wenyu Sun

Zhiqiang Lang, Jiangtao Nie, Wei Wei, Lei Zhang, Yazhe Niu, Peijin Zhuo, Xiangzhen Kong, Long Sun, Wenhao Wang

Swiss Federal Institute of Technology Zurich
Xidian University
Zhejiang University
North China University of Technology
CAS - Institute of Automation
Huawei Technologies Co., Ltd.
Shanghai University
University of California at San Diego
Tsinghua University
Northwestern Polytechnical University Xian
Beihang University
Guilin University of Electronic Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

62 引用（Scopus）

摘要

This paper reviews the AIM 2019 challenge on constrained example-based single image super-resolution with focus on proposed solutions and results. The challenge had 3 tracks. Taking the three main aspects (i.e., number of parameters, inference/running time, fidelity (PSNR)) of MSRResNet as the baseline, Track 1 aims to reduce the amount of parameters while being constrained to maintain or improve the running time and the PSNR result, Tracks 2 and 3 aim to optimize running time and PSNR result with constrain of the other two aspects, respectively. Each track had an average of 64 registered participants, and 12 teams submitted the final results. They gauge the state-of-the-art in single image super-resolution.

源语言	英语
主期刊名	Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019
出版商	Institute of Electrical and Electronics Engineers Inc.
页	3565-3574
页数	10
ISBN（电子版）	9781728150239
DOI	https://doi.org/10.1109/ICCVW.2019.00441
出版状态	已出版 - 10月 2019
已对外发布	是
活动	17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019 - Seoul, 韩国期限: 27 10月 2019 → 28 10月 2019

出版系列

姓名	Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019

会议

会议	17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019
国家/地区	韩国
市	Seoul
时期	27/10/19 → 28/10/19

访问文件

10.1109/ICCVW.2019.00441

其它文件与链接

链接到 Scopus 的出版物

引用此

Zhang, K., Gu, S., Timofte, R., Hui, Z., Wang, X., Gao, X., Xiong, D., Liu, S., Gang, R., Nan, N., Li, C., Zou, X., Kang, N., Wang, Z., Xu, H., Wang, C., Li, Z., Wang, L., Shi, J., ... Wang, W. (2019). AIM 2019 challenge on constrained super-resolution: Methods and results. 在 Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019 (页码 3565-3574). 文章 9022144 (Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCVW.2019.00441

Zhang, Kai ; Gu, Shuhang ; Timofte, Radu 等. / AIM 2019 challenge on constrained super-resolution : Methods and results. Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 页码 3565-3574 (Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019).

@inproceedings{b17e3be9d9e846c1bffa0bdfdc22bfc9,

title = "AIM 2019 challenge on constrained super-resolution: Methods and results",

abstract = "This paper reviews the AIM 2019 challenge on constrained example-based single image super-resolution with focus on proposed solutions and results. The challenge had 3 tracks. Taking the three main aspects (i.e., number of parameters, inference/running time, fidelity (PSNR)) of MSRResNet as the baseline, Track 1 aims to reduce the amount of parameters while being constrained to maintain or improve the running time and the PSNR result, Tracks 2 and 3 aim to optimize running time and PSNR result with constrain of the other two aspects, respectively. Each track had an average of 64 registered participants, and 12 teams submitted the final results. They gauge the state-of-the-art in single image super-resolution.",

keywords = "Constrained super resolution, Super resolution challenge",

author = "Kai Zhang and Shuhang Gu and Radu Timofte and Zheng Hui and Xiumei Wang and Xinbo Gao and Dongliang Xiong and Shuai Liu and Ruipeng Gang and Nan Nan and Chenghua Li and Xueyi Zou and Ning Kang and Zhan Wang and Hang Xu and Chaofeng Wang and Zheng Li and Linlin Wang and Jun Shi and Wenyu Sun and Zhiqiang Lang and Jiangtao Nie and Wei Wei and Lei Zhang and Yazhe Niu and Peijin Zhuo and Xiangzhen Kong and Long Sun and Wenhao Wang",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019 ; Conference date: 27-10-2019 Through 28-10-2019",

year = "2019",

month = oct,

doi = "10.1109/ICCVW.2019.00441",

language = "英语",

series = "Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "3565--3574",

booktitle = "Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019",

}

Zhang, K, Gu, S, Timofte, R, Hui, Z, Wang, X, Gao, X, Xiong, D, Liu, S, Gang, R, Nan, N, Li, C, Zou, X, Kang, N, Wang, Z, Xu, H, Wang, C, Li, Z, Wang, L, Shi, J, Sun, W, Lang, Z, Nie, J, Wei, W, Zhang, L, Niu, Y, Zhuo, P, Kong, X, Sun, L & Wang, W 2019, AIM 2019 challenge on constrained super-resolution: Methods and results. 在 Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019., 9022144, Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019, Institute of Electrical and Electronics Engineers Inc., 页码 3565-3574, 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019, Seoul, 韩国, 27/10/19. https://doi.org/10.1109/ICCVW.2019.00441

AIM 2019 challenge on constrained super-resolution: Methods and results. / Zhang, Kai; Gu, Shuhang; Timofte, Radu 等.
Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 页码 3565-3574 9022144 (Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - AIM 2019 challenge on constrained super-resolution

T2 - 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019

AU - Zhang, Kai

AU - Gu, Shuhang

AU - Timofte, Radu

AU - Hui, Zheng

AU - Wang, Xiumei

AU - Gao, Xinbo

AU - Xiong, Dongliang

AU - Liu, Shuai

AU - Gang, Ruipeng

AU - Nan, Nan

AU - Li, Chenghua

AU - Zou, Xueyi

AU - Kang, Ning

AU - Wang, Zhan

AU - Xu, Hang

AU - Wang, Chaofeng

AU - Li, Zheng

AU - Wang, Linlin

AU - Shi, Jun

AU - Sun, Wenyu

AU - Lang, Zhiqiang

AU - Nie, Jiangtao

AU - Wei, Wei

AU - Zhang, Lei

AU - Niu, Yazhe

AU - Zhuo, Peijin

AU - Kong, Xiangzhen

AU - Sun, Long

AU - Wang, Wenhao

PY - 2019/10

Y1 - 2019/10

N2 - This paper reviews the AIM 2019 challenge on constrained example-based single image super-resolution with focus on proposed solutions and results. The challenge had 3 tracks. Taking the three main aspects (i.e., number of parameters, inference/running time, fidelity (PSNR)) of MSRResNet as the baseline, Track 1 aims to reduce the amount of parameters while being constrained to maintain or improve the running time and the PSNR result, Tracks 2 and 3 aim to optimize running time and PSNR result with constrain of the other two aspects, respectively. Each track had an average of 64 registered participants, and 12 teams submitted the final results. They gauge the state-of-the-art in single image super-resolution.

AB - This paper reviews the AIM 2019 challenge on constrained example-based single image super-resolution with focus on proposed solutions and results. The challenge had 3 tracks. Taking the three main aspects (i.e., number of parameters, inference/running time, fidelity (PSNR)) of MSRResNet as the baseline, Track 1 aims to reduce the amount of parameters while being constrained to maintain or improve the running time and the PSNR result, Tracks 2 and 3 aim to optimize running time and PSNR result with constrain of the other two aspects, respectively. Each track had an average of 64 registered participants, and 12 teams submitted the final results. They gauge the state-of-the-art in single image super-resolution.

KW - Constrained super resolution

KW - Super resolution challenge

UR - https://www.scopus.com/pages/publications/85082445473

U2 - 10.1109/ICCVW.2019.00441

DO - 10.1109/ICCVW.2019.00441

M3 - 会议稿件

AN - SCOPUS:85082445473

T3 - Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019

SP - 3565

EP - 3574

BT - Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 27 October 2019 through 28 October 2019

ER -

Zhang K, Gu S, Timofte R, Hui Z, Wang X, Gao X 等. AIM 2019 challenge on constrained super-resolution: Methods and results. 在 Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 页码 3565-3574. 9022144. (Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019). doi: 10.1109/ICCVW.2019.00441

AIM 2019 challenge on constrained super-resolution: Methods and results

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