AIM 2019 challenge on image demoireing: Methods and results

Shanxin Yuan; Radu Timofte; Greg Slabaugh; Ales Leonardis; Bolun Zheng; Xin Ye; Xiang Tian; Yaowu Chen; Xi Cheng; Zhenyong Fu; Jian Yang; Ming Hong; Wenying Lin; Wenjin Yang; Yanyun Qu; Hong Kyu Shin; Joon Yeon Kim; Sung Jea Ko; Hang Dong; Yu Guo; Jie Wang; Xuan Ding; Zongyan Han; Sourya DIpta Das; Kuldeep Purohit; Praveen Kandula; Maitreya Suin; A. N. Rajagoapalan

doi:10.1109/ICCVW.2019.00438

AIM 2019 challenge on image demoireing: Methods and results

Shanxin Yuan
, Radu Timofte
, Greg Slabaugh
, Ales Leonardis
, Bolun Zheng
, Xin Ye
, Xiang Tian
, Yaowu Chen
, Xi Cheng
, Zhenyong Fu
, Jian Yang
, Ming Hong
, Wenying Lin
, Wenjin Yang
, Yanyun Qu
, Hong Kyu Shin
, Joon Yeon Kim
, Sung Jea Ko
, Hang Dong
, Yu Guo

Jie Wang, Xuan Ding, Zongyan Han, Sourya DIpta Das, Kuldeep Purohit, Praveen Kandula, Maitreya Suin, A. N. Rajagoapalan

College of Artificial Intelligence and Robotics

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

49 Scopus citations

Abstract

This paper reviews the first-ever image demoireing challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ICCV 2019. This paper describes the challenge, and focuses on the proposed solutions and their results. Demoireing is a difficult task of removing moire patterns from an image to reveal an underlying clean image. A new dataset, called LCDMoire was created for this challenge, and consists of 10,200 synthetically generated image pairs (moire and clean ground truth). The challenge was divided into 2 tracks. Track 1 targeted fidelity, measuring the ability of demoire methods to obtain a moire-free image compared with the ground truth, while Track 2 examined the perceptual quality of demoire methods. The tracks had 60 and 39 registered participants, respectively. A total of eight teams competed in the final testing phase. The entries span the current the state-of-the-art in the image demoireing problem.

Original language	English
Title of host publication	Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3534-3545
Number of pages	12
ISBN (Electronic)	9781728150239
DOIs	https://doi.org/10.1109/ICCVW.2019.00438
State	Published - Oct 2019
Event	17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019 - Seoul, Korea, Republic of Duration: 27 Oct 2019 → 28 Oct 2019

Publication series

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

Conference

Conference	17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019
Country/Territory	Korea, Republic of
City	Seoul
Period	27/10/19 → 28/10/19

Keywords

AIM
Challenge
Demoireing
Methods
Results

Access to Document

10.1109/ICCVW.2019.00438

Cite this

Yuan, S., Timofte, R., Slabaugh, G., Leonardis, A., Zheng, B., Ye, X., Tian, X., Chen, Y., Cheng, X., Fu, Z., Yang, J., Hong, M., Lin, W., Yang, W., Qu, Y., Shin, H. K., Kim, J. Y., Ko, S. J., Dong, H., ... Rajagoapalan, A. N. (2019). AIM 2019 challenge on image demoireing: Methods and results. In Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019 (pp. 3534-3545). Article 9022366 (Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCVW.2019.00438

@inproceedings{2804014acb434bee8a798f6537ff3589,

title = "AIM 2019 challenge on image demoireing: Methods and results",

abstract = "This paper reviews the first-ever image demoireing challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ICCV 2019. This paper describes the challenge, and focuses on the proposed solutions and their results. Demoireing is a difficult task of removing moire patterns from an image to reveal an underlying clean image. A new dataset, called LCDMoire was created for this challenge, and consists of 10,200 synthetically generated image pairs (moire and clean ground truth). The challenge was divided into 2 tracks. Track 1 targeted fidelity, measuring the ability of demoire methods to obtain a moire-free image compared with the ground truth, while Track 2 examined the perceptual quality of demoire methods. The tracks had 60 and 39 registered participants, respectively. A total of eight teams competed in the final testing phase. The entries span the current the state-of-the-art in the image demoireing problem.",

keywords = "AIM, Challenge, Demoireing, Methods, Results",

author = "Shanxin Yuan and Radu Timofte and Greg Slabaugh and Ales Leonardis and Bolun Zheng and Xin Ye and Xiang Tian and Yaowu Chen and Xi Cheng and Zhenyong Fu and Jian Yang and Ming Hong and Wenying Lin and Wenjin Yang and Yanyun Qu and Shin, \{Hong Kyu\} and Kim, \{Joon Yeon\} and Ko, \{Sung Jea\} and Hang Dong and Yu Guo and Jie Wang and Xuan Ding and Zongyan Han and Das, \{Sourya DIpta\} and Kuldeep Purohit and Praveen Kandula and Maitreya Suin and Rajagoapalan, \{A. N.\}",

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.2019.00438",

language = "英语",

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

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

pages = "3534--3545",

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

}

Yuan, S, Timofte, R, Slabaugh, G, Leonardis, A, Zheng, B, Ye, X, Tian, X, Chen, Y, Cheng, X, Fu, Z, Yang, J, Hong, M, Lin, W, Yang, W, Qu, Y, Shin, HK, Kim, JY, Ko, SJ, Dong, H, Guo, Y, Wang, J, Ding, X, Han, Z, Das, SDI, Purohit, K, Kandula, P, Suin, M & Rajagoapalan, AN 2019, AIM 2019 challenge on image demoireing: Methods and results. in Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019., 9022366, Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019, Institute of Electrical and Electronics Engineers Inc., pp. 3534-3545, 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019, Seoul, Korea, Republic of, 27/10/19. https://doi.org/10.1109/ICCVW.2019.00438

AIM 2019 challenge on image demoireing: Methods and results. / Yuan, Shanxin; Timofte, Radu; Slabaugh, Greg et al.
Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 3534-3545 9022366 (Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019).

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

TY - GEN

T1 - AIM 2019 challenge on image demoireing

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

AU - Yuan, Shanxin

AU - Timofte, Radu

AU - Slabaugh, Greg

AU - Leonardis, Ales

AU - Zheng, Bolun

AU - Ye, Xin

AU - Tian, Xiang

AU - Chen, Yaowu

AU - Cheng, Xi

AU - Fu, Zhenyong

AU - Yang, Jian

AU - Hong, Ming

AU - Lin, Wenying

AU - Yang, Wenjin

AU - Qu, Yanyun

AU - Shin, Hong Kyu

AU - Kim, Joon Yeon

AU - Ko, Sung Jea

AU - Dong, Hang

AU - Guo, Yu

AU - Wang, Jie

AU - Ding, Xuan

AU - Han, Zongyan

AU - Das, Sourya DIpta

AU - Purohit, Kuldeep

AU - Kandula, Praveen

AU - Suin, Maitreya

AU - Rajagoapalan, A. N.

PY - 2019/10

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N2 - This paper reviews the first-ever image demoireing challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ICCV 2019. This paper describes the challenge, and focuses on the proposed solutions and their results. Demoireing is a difficult task of removing moire patterns from an image to reveal an underlying clean image. A new dataset, called LCDMoire was created for this challenge, and consists of 10,200 synthetically generated image pairs (moire and clean ground truth). The challenge was divided into 2 tracks. Track 1 targeted fidelity, measuring the ability of demoire methods to obtain a moire-free image compared with the ground truth, while Track 2 examined the perceptual quality of demoire methods. The tracks had 60 and 39 registered participants, respectively. A total of eight teams competed in the final testing phase. The entries span the current the state-of-the-art in the image demoireing problem.

AB - This paper reviews the first-ever image demoireing challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ICCV 2019. This paper describes the challenge, and focuses on the proposed solutions and their results. Demoireing is a difficult task of removing moire patterns from an image to reveal an underlying clean image. A new dataset, called LCDMoire was created for this challenge, and consists of 10,200 synthetically generated image pairs (moire and clean ground truth). The challenge was divided into 2 tracks. Track 1 targeted fidelity, measuring the ability of demoire methods to obtain a moire-free image compared with the ground truth, while Track 2 examined the perceptual quality of demoire methods. The tracks had 60 and 39 registered participants, respectively. A total of eight teams competed in the final testing phase. The entries span the current the state-of-the-art in the image demoireing problem.

KW - AIM

KW - Challenge

KW - Demoireing

KW - Methods

KW - Results

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U2 - 10.1109/ICCVW.2019.00438

DO - 10.1109/ICCVW.2019.00438

M3 - 会议稿件

AN - SCOPUS:85082495304

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

SP - 3534

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

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Yuan S, Timofte R, Slabaugh G, Leonardis A, Zheng B, Ye X et al. AIM 2019 challenge on image demoireing: Methods and results. In Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 3534-3545. 9022366. (Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019). doi: 10.1109/ICCVW.2019.00438

AIM 2019 challenge on image demoireing: Methods and results

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Keywords

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