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Chu-Style Lacquerware Dataset: A Dataset for Digital Preservation and Inheritance of Chu-Style Lacquerware.

Haoming Bi1, Yelei Chen1, Chanjuan Chen1

  • 1Digital Art Industry Institute, Hubei University of Technology, Wuhan 430068, China.

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Summary
This summary is machine-generated.

This study introduces the Chu-style lacquerware (CSL) dataset for digital preservation. The CSL dataset enhances AI-generated images and innovative patterns, supporting cultural heritage and interdisciplinary research.

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Chu-style lacquerwareartificial intelligence-generated modeldigital preservation and inheritance of traditional Chinese craftsintangible cultural heritage preservationlow-rank adaptation training technique

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Area of Science:

  • Digital Humanities
  • Artificial Intelligence
  • Cultural Heritage Preservation

Background:

  • Chu-style lacquerware (CSL) is a vital part of global intangible handicraft heritage.
  • Digital preservation is crucial for safeguarding and transmitting CSL.

Purpose of the Study:

  • To develop a dedicated dataset for AI generative models of CSL.
  • To validate the CSL dataset's usability for digital preservation and cultural dissemination.

Main Methods:

  • Integrated on-site images and digital resources to create the CSL dataset.
  • Employed Low-Rank Adaptation (LoRA) to train AI models using the CSL dataset.
  • Verified dataset usability through five aspects, focusing on AI-generated image quality.

Main Results:

  • The CSL dataset improved accuracy and detail restoration in AI-generated CSL images.
  • Optimized generative effects for innovative patterns based on CSL.
  • Validated the dataset's application value in cultural heritage AI generation.

Conclusions:

  • The CSL dataset offers a novel technological pathway for digital preservation of cultural heritage.
  • Supports interdisciplinary research in archaeology, art history, and cultural communication.
  • Highlights the significance of cross-disciplinary collaboration for Intangible Cultural Heritage (ICH) safeguarding.