Chinese Opera Character Painting Style Transfer: Using AI to Generate and Preserve Art

Xirong Gao, Liza Mohammad Noh and Zhongwei Huang
Additional contact information
Xirong Gao: College of Creative Arts, University Teknologi MARA (UiTM), Shah Alam, Selangor Darul Ehsan, Malaysia
Liza Mohammad Noh: College of Creative Arts, University Teknologi MARA (UiTM), Shah Alam, Selangor Darul Ehsan, Malaysia
Zhongwei Huang: School of Computer Science and Engineering, Macau University of Science and Technology

International Journal of Research and Innovation in Social Science, 2024, vol. 8, issue 3s, 5724-5731

Abstract: Chinese Opera characters ink painting, a distinctive blend of Chinese color ink painting and traditional opera, reflects the rich aesthetic heritage of Chinese culture. The advent of Artificial Intelligence Generated Content (AIGC) technology presents new opportunities for preserving and innovating this traditional art form. While style transfer techniques have been widely applied to Western art, the freehand style of Chinese ink painting remains under-explored. This paper fills this gap by constructing datasets of Chinese Opera character paintings through field visits and web crawling. This paper develops an automated system for transforming realistic opera character images into Chinese opera character paintings by leveraging generative adversarial networks (GAN) technology. The generated results prove that the GAN-based model is able to learn the key features of a style image and be able to distinguish the relationship between people in the image, it is better than an ordinary person with no foundation would draw. This research advances AI’s application in traditional art and provides a new thought to the preservation, dissemination, and modern reinterpretation of Chinese Opera characters ink painting.

Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.rsisinternational.org/journals/ijriss/ ... sue-3s/5724-5731.pdf (application/pdf)
https://rsisinternational.org/journals/ijriss/arti ... te-and-preserve-art/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bcp:journl:v:8:y:2024:i:3s:p:5724-5731

Access Statistics for this article

International Journal of Research and Innovation in Social Science is currently edited by Dr. Nidhi Malhan

More articles in International Journal of Research and Innovation in Social Science from International Journal of Research and Innovation in Social Science (IJRISS)
Bibliographic data for series maintained by Dr. Pawan Verma ().