Enhancing the Digital Inheritance and Development of Chinese Intangible Cultural Heritage Paper-Cutting Through Stable Diffusion LoRA Models

With the advent of artificial intelligence digitization, intangible cultural heritage faces challenges in preservation and transmission. Utilizing modern technology to achieve digital protection and dissemination has become a crucial issue today. This study enhances the digital inheritance and development of Chinese intangible cultural heritage paper-cutting art through generative AI technologies, specifically Diffusion and LoRA models. The Analytic Hierarchy Process (AHP) was employed to categorize the cultural value of paper-cutting, selecting four core elements: “Spring Festival”, “Chinese Zodiac”, “Women”, and “Birds and Flowers”. Based on these, eight LoRA models were developed to generate paper-cutting-style patterns (using the FLUX.1-dev and Stable Diffusion 1.5 models). In the user satisfaction assessment, the Importance–Performance Analysis (IPA) method was used to analyze four dimensions of the model experience. The results indicate that the LoRA model excels in generating detailed paper-cutting patterns and accurately reproducing cultural elements, particularly in the generation of complex Chinese character designs. User feedback suggests that the LoRA model effectively enhances the digital representation and dissemination of paper-cutting art, though there is room for improvement in terms of generation speed and ease of operation. This study provides a new technological pathway for the digital preservation of intangible cultural heritage and promotes the modernization of paper-cutting art transmission.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2024-11-27
DOI
https://doi.org/10.3390/app142311032
Citations
30
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
25.04
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing the Digital Inheritance and Development of Chinese Intangible Cultural Heritage Paper-Cutting Through Stable Diffusion LoRA Models

Jung-Ho Jung, Runqi Wang, Mengge Dai, Yuhao Feng
30 citations
Applied Sciences
3D Surveying and Cultural Heritage
25.04
article

Enhancing the Digital Inheritance and Development of Chinese Intangible Cultural Heritage Paper-Cutting Through Stable Diffusion LoRA Models

Jung-Ho Jung, Runqi Wang, Mengge Dai, Yuhao Feng
article en
30 citations

Abstract

With the advent of artificial intelligence digitization, intangible cultural heritage faces challenges in preservation and transmission. Utilizing modern technology to achieve digital protection and dissemination has become a crucial issue today. This study enhances the digital inheritance and development of Chinese intangible cultural heritage paper-cutting art through generative AI technologies, specifically Diffusion and LoRA models. The Analytic Hierarchy Process (AHP) was employed to categorize the cultural value of paper-cutting, selecting four core elements: “Spring Festival”, “Chinese Zodiac”, “Women”, and “Birds and Flowers”. Based on these, eight LoRA models were developed to generate paper-cutting-style patterns (using the FLUX.1-dev and Stable Diffusion 1.5 models). In the user satisfaction assessment, the Importance–Performance Analysis (IPA) method was used to analyze four dimensions of the model experience. The results indicate that the LoRA model excels in generating detailed paper-cutting patterns and accurately reproducing cultural elements, particularly in the generation of complex Chinese character designs. User feedback suggests that the LoRA model effectively enhances the digital representation and dissemination of paper-cutting art, though there is room for improvement in terms of generation speed and ease of operation. This study provides a new technological pathway for the digital preservation of intangible cultural heritage and promotes the modernization of paper-cutting art transmission.

Applied SciencesVol. 14(23)
Chonnam National University (KR)
Sustainable cities and communities
Openalex Percentile: Top 0%
3D Surveying and Cultural Heritage
25.04
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.