The frontier research topics on artificial intelligence empowering cultural heritage conservation and inheritance

• Published in: Geographical Research Bulletin Vol. 4; pp. 503 - 506
• Main Authors: Qiu, Sue, Tao, Yirong, Yang, Zhongchuan
• Format: Journal Article
• Language: English; Japanese
• Published: Resources Economics Research Board 30.07.2025
• Subjects: cultural heritage conservation; generative adversarial networks; intangible cultural heritage; knowledge graph; reinforcement learning
• ISSN: 2758-1446
• DOI: 10.50908/grb.4.0_503

With the rapid advancement of artificial intelligence (AI), cultural heritage conservation and inheritance have entered a new stage characterized by intelligence and systematization. This paper systematically explores the multifaceted applications of AI in the field of cultural heritage, focusing on four representative frontier research topics. First, cultural heritage restoration and digital revitalization based on generative adversarial networks and diffusion models are driving a shift from physical repair to intelligent reconstruction, emphasizing stylistic consistency and semantic restoration. Second, multimodal AI-powered technologies for the recognition and documentation of intangible cultural heritage integrate speech, vision, and language to achieve fine-grained perception and structured representation of dynamic cultural expressions. Third, reinforcement learning-driven intelligent management systems offer efficient and sustainable decision support for visitor flow regulation, microenvironment control, and immersive guiding at heritage sites. Fourth, cross-lingual and cross-cultural knowledge graphs and intelligent question-answering systems break down information barriers, enabling the global sharing and integration of cultural heritage resources. By analyzing these key topics, this paper aims to reveal the theoretical progress and technological trends in AI-empowered cultural heritage conservation, providing systematic insights and theoretical support for interdisciplinary development and future research in the field.