OracleSage: Towards Unified Visual-Linguistic Understanding of Oracle Bone Scripts through Cross-Modal Knowledge Fusion

Hanqi Jiang, Yi Pan, Junhao Chen, Zhengliang Liu, Yifan Zhou +6 more
11/26/2024
cs.CV

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Abstract

Oracle bone script (OBS), as China's earliest mature writing system, present significant challenges in automatic recognition due to their complex pictographic structures and divergence from modern Chinese characters. We introduce OracleSage, a novel cross-modal framework that integrates hierarchical visual understanding with graph-based semantic reasoning. Specifically, we propose (1) a Hierarchical Visual-Semantic Understanding module that enables multi-granularity feature extraction through progressive fine-tuning of LLaVA's visual backbone, (2) a Graph-based Semantic Reasoning Framework that captures relationships between visual components and semantic concepts through dynamic message passing, and (3) OracleSem, a semantically enriched OBS dataset with comprehensive pictographic and semantic annotations. Experimental results demonstrate that OracleSage significantly outperforms state-of-the-art vision-language models. This research establishes a new paradigm for ancient text interpretation while providing valuable technical support for archaeological studies.

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Cite this paper

@article{jiang2024oraclesage,
  title  = {OracleSage: Towards Unified Visual-Linguistic Understanding of Oracle Bone Scripts through Cross-Modal Knowledge Fusion},
  author = {Hanqi Jiang and Yi Pan and Junhao Chen and Zhengliang Liu and Yifan Zhou and Peng Shu and Yiwei Li and Huaqin Zhao and Stephen Mihm and Lewis C Howe and Tianming Liu},
  year   = {2024},
  eprint = {2411.17837},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2411.17837v1}
}

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