Generative AI for Cultural Heritage: Shanghai Revolutionary Culture Digital Design Based on the SD–LoRA Model

In recent years, the development of generative artificial intelligence, particularly diffusion models such as Stable Diffusion (SD), has provided new opportunities for the digital representation and creative dissemination of cultural heritage. This study takes Shanghai revolutionary cultural heritage as a case study and develops an application-oriented integrated workflow for generating revolutionary cultural images. By introducing Low-Rank Adaptation (LoRA) into the SD framework and combining structural control with local refinement strategies, this study enhances the style expression and structural quality of the generated images. Furthermore, an interactive creation platform is constructed to support the generation and creation of revolutionary cultural images. The evaluation results, including subjective assessment and SSIM/LPIPS metrics, indicate that the proposed workflow achieves higher style consistency and structural reliability while improving the structural integrity and detail reliability of facial regions. The proposed workflow and platform are intended to support revolutionary cultural venues in practical digital production and dissemination of heritage content while also promoting public engagement with revolutionary culture, especially among younger audiences. This study highlights the application potential of generative Artificial Intelligence (AI) in enhancing the accessibility, digitalization, and sustainable dissemination of revolutionary cultural heritage. It also provides a practical reference for interdisciplinary research in the field of cultural heritage and AI-assisted digital communication.

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Publication Details

Journal
Applied Sciences
Published
2026-05-01
DOI
https://doi.org/10.3390/app16094427
Primary Topic
Generative Adversarial Networks and Image Synthesis
Type
article
Field-Weighted Citation Impact
0.00

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article

Generative AI for Cultural Heritage: Shanghai Revolutionary Culture Digital Design Based on the SD–LoRA Model

Ling Tong, Chunmao Wu, Jian Tang
Applied Sciences
Generative Adversarial Networks and Image Synthesis
article

Generative AI for Cultural Heritage: Shanghai Revolutionary Culture Digital Design Based on the SD–LoRA Model

Ling Tong, Chunmao Wu, Jian Tang
article en

Abstract

In recent years, the development of generative artificial intelligence, particularly diffusion models such as Stable Diffusion (SD), has provided new opportunities for the digital representation and creative dissemination of cultural heritage. This study takes Shanghai revolutionary cultural heritage as a case study and develops an application-oriented integrated workflow for generating revolutionary cultural images. By introducing Low-Rank Adaptation (LoRA) into the SD framework and combining structural control with local refinement strategies, this study enhances the style expression and structural quality of the generated images. Furthermore, an interactive creation platform is constructed to support the generation and creation of revolutionary cultural images. The evaluation results, including subjective assessment and SSIM/LPIPS metrics, indicate that the proposed workflow achieves higher style consistency and structural reliability while improving the structural integrity and detail reliability of facial regions. The proposed workflow and platform are intended to support revolutionary cultural venues in practical digital production and dissemination of heritage content while also promoting public engagement with revolutionary culture, especially among younger audiences. This study highlights the application potential of generative Artificial Intelligence (AI) in enhancing the accessibility, digitalization, and sustainable dissemination of revolutionary cultural heritage. It also provides a practical reference for interdisciplinary research in the field of cultural heritage and AI-assisted digital communication.

Applied SciencesVol. 16(9)
Donghua University (CN)
Fundamental Research Funds for the Central Universities
Sustainable cities and communities
Openalex Percentile: Top 7%
Generative Adversarial Networks and Image Synthesis
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Generative AI for Cultural Heritage: Shanghai Revolutionary Culture Digital Design Based on the SD–LoRA Model — Ling Tong, Chunmao Wu, et al. · Applied Sciences (2026) | TGRS Research Map | TGRS