TSRFormer: Transformer Based Two-stage Refinement for Single Image Shadow Removal

Hua En Chang; Chia Hsuan Hsieh; Hao Hsiang Yang; I. Hsiang Chen; Yi Chung Chen; Yuan Chun Chiang; Zhi Kai Huang; Wei Ting Chen; Sy Yen Kuo

doi:10.1109/CVPRW59228.2023.00148

TSRFormer: Transformer Based Two-stage Refinement for Single Image Shadow Removal

Hua En Chang^*
, Chia Hsuan Hsieh^*
, Hao Hsiang Yang
, I. Hsiang Chen
, Yi Chung Chen
, Yuan Chun Chiang
, Zhi Kai Huang
, Wei Ting Chen
, Sy Yen Kuo

^*此作品的通信作者

研究成果: 圖書/報告稿件的類型 › 會議稿件 › 同行評審

10 引文斯高帕斯（Scopus）

摘要

Single-image shadow removal aims to remove undesired shadow information from captured images. With the development of deep convolutional neural networks, several methods have been proposed to achieve promising performance in shadow removal. However, they still struggle with limited performance due to the non-homogeneous intensity distribution of the shadow. To address this issue, we propose a two-stage shadow removal architecture based on the transformer called TSRFormer. The proposed architecture is divided into shadow removal and content refinement networks. These two stages adopt different transformer architectures and remove the shadow based on different information to achieve effective shadow removal. Experiments performed on challenging benchmark show that the proposed model achieves the 2nd highest SSIM in the NTIRE 2023 Image Shadow Removal Challenge. The source code will be public after the acceptance of this paper.

原文	英語
主出版物標題	Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023
發行者	IEEE Computer Society
頁面	1436-1446
頁數	11
ISBN（電子）	9798350302493
DOIs	https://doi.org/10.1109/CVPRW59228.2023.00148
出版狀態	已出版 - 2023
對外發佈	是
事件	2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023 - Vancouver, 加拿大持續時間: 18 06 2023 → 22 06 2023

出版系列

名字	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
卷	2023-June
ISSN（列印）	2160-7508
ISSN（電子）	2160-7516

Conference

Conference	2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023
國家/地區	加拿大
城市	Vancouver
期間	18/06/23 → 22/06/23

文獻附註

Publisher Copyright:
© 2023 IEEE.

存取文件

10.1109/CVPRW59228.2023.00148

其它文件與鏈接

Link to publication in Scopus

引用此

Chang, H. E., Hsieh, C. H., Yang, H. H., Chen, I. H., Chen, Y. C., Chiang, Y. C., Huang, Z. K., Chen, W. T., & Kuo, S. Y. (2023). TSRFormer: Transformer Based Two-stage Refinement for Single Image Shadow Removal. 於 Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023 (頁 1436-1446). (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; 卷 2023-June). IEEE Computer Society. https://doi.org/10.1109/CVPRW59228.2023.00148

Chang, Hua En ; Hsieh, Chia Hsuan ; Yang, Hao Hsiang 等. / TSRFormer : Transformer Based Two-stage Refinement for Single Image Shadow Removal. Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023. IEEE Computer Society, 2023. 頁 1436-1446 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops).

@inproceedings{38bf4ee6393f4a4aa8310d589eb4aec6,

title = "TSRFormer: Transformer Based Two-stage Refinement for Single Image Shadow Removal",

abstract = "Single-image shadow removal aims to remove undesired shadow information from captured images. With the development of deep convolutional neural networks, several methods have been proposed to achieve promising performance in shadow removal. However, they still struggle with limited performance due to the non-homogeneous intensity distribution of the shadow. To address this issue, we propose a two-stage shadow removal architecture based on the transformer called TSRFormer. The proposed architecture is divided into shadow removal and content refinement networks. These two stages adopt different transformer architectures and remove the shadow based on different information to achieve effective shadow removal. Experiments performed on challenging benchmark show that the proposed model achieves the 2nd highest SSIM in the NTIRE 2023 Image Shadow Removal Challenge. The source code will be public after the acceptance of this paper.",

author = "Chang, \{Hua En\} and Hsieh, \{Chia Hsuan\} and Yang, \{Hao Hsiang\} and Chen, \{I. Hsiang\} and Chen, \{Yi Chung\} and Chiang, \{Yuan Chun\} and Huang, \{Zhi Kai\} and Chen, \{Wei Ting\} and Kuo, \{Sy Yen\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023 ; Conference date: 18-06-2023 Through 22-06-2023",

year = "2023",

doi = "10.1109/CVPRW59228.2023.00148",

language = "英语",

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

publisher = "IEEE Computer Society",

pages = "1436--1446",

booktitle = "Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023",

address = "美国",

}

Chang, HE, Hsieh, CH, Yang, HH, Chen, IH, Chen, YC, Chiang, YC, Huang, ZK, Chen, WT & Kuo, SY 2023, TSRFormer: Transformer Based Two-stage Refinement for Single Image Shadow Removal. 於 Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 卷 2023-June, IEEE Computer Society, 頁 1436-1446, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023, Vancouver, 加拿大, 18/06/23. https://doi.org/10.1109/CVPRW59228.2023.00148

TSRFormer: Transformer Based Two-stage Refinement for Single Image Shadow Removal. / Chang, Hua En; Hsieh, Chia Hsuan; Yang, Hao Hsiang 等.
Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023. IEEE Computer Society, 2023. p. 1436-1446 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; 卷 2023-June).

研究成果: 圖書/報告稿件的類型 › 會議稿件 › 同行評審

TY - GEN

T1 - TSRFormer

T2 - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023

AU - Chang, Hua En

AU - Hsieh, Chia Hsuan

AU - Yang, Hao Hsiang

AU - Chen, I. Hsiang

AU - Chen, Yi Chung

AU - Chiang, Yuan Chun

AU - Huang, Zhi Kai

AU - Chen, Wei Ting

AU - Kuo, Sy Yen

PY - 2023

Y1 - 2023

N2 - Single-image shadow removal aims to remove undesired shadow information from captured images. With the development of deep convolutional neural networks, several methods have been proposed to achieve promising performance in shadow removal. However, they still struggle with limited performance due to the non-homogeneous intensity distribution of the shadow. To address this issue, we propose a two-stage shadow removal architecture based on the transformer called TSRFormer. The proposed architecture is divided into shadow removal and content refinement networks. These two stages adopt different transformer architectures and remove the shadow based on different information to achieve effective shadow removal. Experiments performed on challenging benchmark show that the proposed model achieves the 2nd highest SSIM in the NTIRE 2023 Image Shadow Removal Challenge. The source code will be public after the acceptance of this paper.

AB - Single-image shadow removal aims to remove undesired shadow information from captured images. With the development of deep convolutional neural networks, several methods have been proposed to achieve promising performance in shadow removal. However, they still struggle with limited performance due to the non-homogeneous intensity distribution of the shadow. To address this issue, we propose a two-stage shadow removal architecture based on the transformer called TSRFormer. The proposed architecture is divided into shadow removal and content refinement networks. These two stages adopt different transformer architectures and remove the shadow based on different information to achieve effective shadow removal. Experiments performed on challenging benchmark show that the proposed model achieves the 2nd highest SSIM in the NTIRE 2023 Image Shadow Removal Challenge. The source code will be public after the acceptance of this paper.

UR - https://www.scopus.com/pages/publications/85170826284

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DO - 10.1109/CVPRW59228.2023.00148

M3 - 会议稿件

AN - SCOPUS:85170826284

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

SP - 1436

EP - 1446

BT - Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023

PB - IEEE Computer Society

Y2 - 18 June 2023 through 22 June 2023

ER -

Chang HE, Hsieh CH, Yang HH, Chen IH, Chen YC, Chiang YC 等. TSRFormer: Transformer Based Two-stage Refinement for Single Image Shadow Removal. 於 Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023. IEEE Computer Society. 2023. p. 1436-1446. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). doi: 10.1109/CVPRW59228.2023.00148

TSRFormer: Transformer Based Two-stage Refinement for Single Image Shadow Removal

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