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

Shuo Zhao, Yifei Huang, Xiaoyang He, Xin Tong, Xin Li, and Dan Wu

Abstract

A generative AI-powered pipeline is introduced to automate mural recreation in VR, overcoming the challenges of traditional hand-crafted methods. A user study on Dunhuang Murals found no significant differences in presence, authenticity, or engagement between AI-generated and hand

Abstract

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.

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