An archaeological Catalog Collection Method Based on Large Vision-Language Models

• URL: http://arxiv.org/abs/2412.20088v1
• Date: Sat, 28 Dec 2024 09:10:41 GMT
• Title: An archaeological Catalog Collection Method Based on Large Vision-Language Models
• Authors: Honglin Pang, Yi Chang, Tianjing Duan, Xi Yang,
• Abstract summary: Archaeological catalogs, containing key elements such as artifact images, morphological descriptions, and excavation information, are essential for studying artifact evolution and cultural inheritance. Existing Large Vision-Language Models and their derivative data collection methods face challenges in accurate image detection and modal matching. We propose a novel archaeological catalog collection method based on Large Vision-Language Models that follows an approach comprising three modules: document localization, block comprehension and block matching.
• Score: 9.177297031425859
• License:
• Abstract: Archaeological catalogs, containing key elements such as artifact images, morphological descriptions, and excavation information, are essential for studying artifact evolution and cultural inheritance. These data are widely scattered across publications, requiring automated collection methods. However, existing Large Vision-Language Models (VLMs) and their derivative data collection methods face challenges in accurate image detection and modal matching when processing archaeological catalogs, making automated collection difficult. To address these issues, we propose a novel archaeological catalog collection method based on Large Vision-Language Models that follows an approach comprising three modules: document localization, block comprehension and block matching. Through practical data collection from the Dabagou and Miaozigou pottery catalogs and comparison experiments, we demonstrate the effectiveness of our approach, providing a reliable solution for automated collection of archaeological catalogs.

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