Reviving Mural Art through Generative AI: A Comparative Study of AI-Generated and Hand-Crafted Recreations

要旨

Virtual reality (VR) provides an immersive and interactive platform for presenting ancient murals, enhancing users' understanding and appreciation of these invaluable culture treasures. However, traditional hand-crafted methods for recreating murals in VR are labor-intensive, time-consuming, and require significant expertise, limiting their scalability for large-scale mural scenes. To address these challenges, we propose a comprehensive pipeline that leverages generative AI to automate the mural recreation process. This pipeline is validated by the reconstruction of Foguang Temple scene in Dunhuang Murals. A user study comparing the AI-generated scene with a hand-crafted one reveals no significant differences in presence, authenticity, engagement and enjoyment, and emotion. Additionally, our findings identify areas for improvement in AI-generated recreations, such as enhancing historical fidelity and offering customization. This work paves the way for more scalable, efficient, and accessible methods of revitalizing cultural heritage in VR, offering new opportunities for mural preservation, demonstration, and dissemination using VR.

著者
Shuo Zhao
Duke Kunshan University, Kunshan, Soochow, China
Yifei Huang
Duke Kunshan University, Kunshan, China
Xiaoyang He
School of Information Management, Wuhan, Hubei, China
Xin Tong
Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China
Xin Li
Duke Kunshan University, Kunshan, China
Dan Wu
Wuhan University, Wuhan, China
DOI

10.1145/3706598.3714157

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714157

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Learning, Creating, and Understanding Art

G416+G417
7 件の発表
2025-04-30 20:10:00
2025-04-30 21:40:00
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