PaddleOCR 3.0用小模型实现高效多语言文档理解
PaddleOCR 3.0 Technical Report
- 采用轻量级模型实现多语言文字识别与文档结构解析
- 百万元级参数模型达到千万元级大模型的识别精度
- 支持跨硬件部署，适合开发智能文档应用的开发者
本技术报告介绍 PaddleOCR 3.0，一个 Apache 许可的开源工具包，用于 OCR 和文档解析。为应对大语言模型时代对文档理解日益增长的需求，PaddleOCR 3.0 提出三大解决方案：(1) PP-OCRv5 实现多语言文本识别，(2) PP-StructureV3 支持层次化文档解析，(3) PP-ChatOCRv4 用于关键信息抽取。相比主流视觉语言模型（VLMs），这些模型参数少于 1 亿，在准确率和效率上表现优异，媲美数十亿参数的 VLMs。除提供高质量的 OCR 模型库外，还配备高效的训练、推理与部署工具，支持异构硬件加速，帮助开发者便捷构建智能文档应用。
原文摘要 · Abstract (English)
This technical report introduces PaddleOCR 3.0, an Apache-licensed open-source toolkit for OCR and document parsing. To address the growing demand for document understanding in the era of large language models, PaddleOCR 3.0 presents three major solutions: (1) PP-OCRv5 for multilingual text recognition, (2) PP-StructureV3 for hierarchical document parsing, and (3) PP-ChatOCRv4 for key information extraction. Compared to mainstream vision-language models (VLMs), these models with fewer than 100 million parameters achieve competitive accuracy and efficiency, rivaling billion-parameter VLMs. In addition to offering a high-quality OCR model library, PaddleOCR 3.0 provides efficient tools for training, inference, and deployment, supports heterogeneous hardware acceleration, and enables developers to easily build intelligent document applications.
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