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.
Wu et al. (Fri,) studied this question.