An interactive and generative approach for Chinese Shanshui painting document

Le Zhou; Qiu Feng Wang; Kaizhu Huang; Cheng Hung Lo

doi:10.1109/ICDAR.2019.00136

An interactive and generative approach for Chinese Shanshui painting document

Le Zhou, Qiu Feng Wang, Kaizhu Huang, Cheng Hung Lo

Xi'an Jiaotong-Liverpool University

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

23 Scopus citations

Abstract

Chinese Shanshui is a landscape painting document mainly drawing mountain and water, which is popular in Chinese culture. However, it is very challenging to create this by general people. In this paper, we propose an interactive and generative approach to automatically generate the Chinese Shanshui painting documents based on users' input, where the users only need to sketch simple lines to represent their ideal landscape without any professional Shanshui painting skills. This sketch-to-Shanshui translation is optimized by the model of cycle Generative Adversarial Networks (GAN). To evaluate the proposed approach, we collected a large set of both sketch data and Chinese Shanshui painting data to train the model of cycle-GAN, and developed an interactive system called Shanshui-DaDA (i.e., Design and Draw with AI) to generate Chinese Shanshui painting documents in real-time. The experimental results show that this system can generate satisfied Chinese Shanshui painting documents by general users.

Original language	English
Title of host publication	Proceedings - 15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019
Publisher	IEEE Computer Society
Pages	819-824
Number of pages	6
ISBN (Electronic)	9781728128610
DOIs	https://doi.org/10.1109/ICDAR.2019.00136
State	Published - 09 2019
Externally published	Yes
Event	15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019 - Sydney, Australia Duration: 20 09 2019 → 25 09 2019

Publication series

Name	Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
ISSN (Print)	1520-5363

Conference

Conference	15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019
Country/Territory	Australia
City	Sydney
Period	20/09/19 → 25/09/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

Chinese Shanshui
Generative Adversarial Networks
Image-to-image Translation
Interactive system
Sketch-to-Shanshui Translation

Access to Document

10.1109/ICDAR.2019.00136

Cite this

Zhou, L., Wang, Q. F., Huang, K., & Lo, C. H. (2019). An interactive and generative approach for Chinese Shanshui painting document. In Proceedings - 15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019 (pp. 819-824). Article 8978182 (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR). IEEE Computer Society. https://doi.org/10.1109/ICDAR.2019.00136

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title = "An interactive and generative approach for Chinese Shanshui painting document",

abstract = "Chinese Shanshui is a landscape painting document mainly drawing mountain and water, which is popular in Chinese culture. However, it is very challenging to create this by general people. In this paper, we propose an interactive and generative approach to automatically generate the Chinese Shanshui painting documents based on users' input, where the users only need to sketch simple lines to represent their ideal landscape without any professional Shanshui painting skills. This sketch-to-Shanshui translation is optimized by the model of cycle Generative Adversarial Networks (GAN). To evaluate the proposed approach, we collected a large set of both sketch data and Chinese Shanshui painting data to train the model of cycle-GAN, and developed an interactive system called Shanshui-DaDA (i.e., Design and Draw with AI) to generate Chinese Shanshui painting documents in real-time. The experimental results show that this system can generate satisfied Chinese Shanshui painting documents by general users.",

keywords = "Chinese Shanshui, Generative Adversarial Networks, Image-to-image Translation, Interactive system, Sketch-to-Shanshui Translation",

author = "Le Zhou and Wang, {Qiu Feng} and Kaizhu Huang and Lo, {Cheng Hung}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019 ; Conference date: 20-09-2019 Through 25-09-2019",

year = "2019",

month = sep,

doi = "10.1109/ICDAR.2019.00136",

language = "英语",

series = "Proceedings of the International Conference on Document Analysis and Recognition, ICDAR",

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Zhou, L, Wang, QF, Huang, K & Lo, CH 2019, An interactive and generative approach for Chinese Shanshui painting document. in Proceedings - 15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019., 8978182, Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, IEEE Computer Society, pp. 819-824, 15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019, Sydney, Australia, 20/09/19. https://doi.org/10.1109/ICDAR.2019.00136

An interactive and generative approach for Chinese Shanshui painting document. / Zhou, Le; Wang, Qiu Feng; Huang, Kaizhu et al.
Proceedings - 15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019. IEEE Computer Society, 2019. p. 819-824 8978182 (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR).

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

TY - GEN

T1 - An interactive and generative approach for Chinese Shanshui painting document

AU - Zhou, Le

AU - Wang, Qiu Feng

AU - Huang, Kaizhu

AU - Lo, Cheng Hung

PY - 2019/9

Y1 - 2019/9

N2 - Chinese Shanshui is a landscape painting document mainly drawing mountain and water, which is popular in Chinese culture. However, it is very challenging to create this by general people. In this paper, we propose an interactive and generative approach to automatically generate the Chinese Shanshui painting documents based on users' input, where the users only need to sketch simple lines to represent their ideal landscape without any professional Shanshui painting skills. This sketch-to-Shanshui translation is optimized by the model of cycle Generative Adversarial Networks (GAN). To evaluate the proposed approach, we collected a large set of both sketch data and Chinese Shanshui painting data to train the model of cycle-GAN, and developed an interactive system called Shanshui-DaDA (i.e., Design and Draw with AI) to generate Chinese Shanshui painting documents in real-time. The experimental results show that this system can generate satisfied Chinese Shanshui painting documents by general users.

AB - Chinese Shanshui is a landscape painting document mainly drawing mountain and water, which is popular in Chinese culture. However, it is very challenging to create this by general people. In this paper, we propose an interactive and generative approach to automatically generate the Chinese Shanshui painting documents based on users' input, where the users only need to sketch simple lines to represent their ideal landscape without any professional Shanshui painting skills. This sketch-to-Shanshui translation is optimized by the model of cycle Generative Adversarial Networks (GAN). To evaluate the proposed approach, we collected a large set of both sketch data and Chinese Shanshui painting data to train the model of cycle-GAN, and developed an interactive system called Shanshui-DaDA (i.e., Design and Draw with AI) to generate Chinese Shanshui painting documents in real-time. The experimental results show that this system can generate satisfied Chinese Shanshui painting documents by general users.

KW - Chinese Shanshui

KW - Generative Adversarial Networks

KW - Image-to-image Translation

KW - Interactive system

KW - Sketch-to-Shanshui Translation

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ER -

Zhou L, Wang QF, Huang K, Lo CH. An interactive and generative approach for Chinese Shanshui painting document. In Proceedings - 15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019. IEEE Computer Society. 2019. p. 819-824. 8978182. (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR). doi: 10.1109/ICDAR.2019.00136

An interactive and generative approach for Chinese Shanshui painting document

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