AccScience Publishing / AC / Online First / DOI: 10.36922/AC025170026
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ARTICLE

Exploring the use of artificial intelligence painting technology to restore the portraits of ancient poets

Yao Song1 ,  Zhuolin Wu1* ,  Lingfang Lan1 ,  Wenjing Sun1 ,  Yunjian Fan1 ,  Zhuan Liu1
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1 Department of Advertising, School of Literature and Journalism, Sichuan University, Chengdu, Sichuan, China
AC, 025170026 https://doi.org/10.36922/AC025170026
Received: 22 April 2025 | Revised: 22 August 2025 | Accepted: 25 August 2025 | Published online: 18 September 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Present mainstream artificial intelligence painting models and platforms exhibit a fundamental difficulty in comprehending the defining characteristics of classical Chinese painting: The emphasis on capturing the spirit (Xie Shen) or evocative essence over literal depiction, as well as its characteristic flattened esthetic paradigm. This paper reviews the evolutionary trajectory of artificial intelligence painting technology and delineates its fundamental principles. By applying this technology to restore ancient poet portraits into three-dimensional lifelike representations, it provides technical pathways and parameter references for poet portrait restoration. This exploration charts novel application paths for artificial intelligence technology, enabling it to contribute more effectively to Chinese cultural studies. Furthermore, utilizing Stable Diffusion to restore ancient poet portraits bridges the psychological distance between historical poets and contemporary audiences, thus advancing the dissemination of ancient Chinese poetry culture.

Keywords
Artificial intelligence painting
Ancient poet
Chinese culture
Funding
None.
Conflict of interest
Yao Song is an Editorial Board Member of this journal, but was not in any way involved in the editorial and peer-review process conducted for this paper, directly or indirectly. Separately, other authors declared that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.
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