# MinerU: An Open-Source Solution for Precise Document Content Extraction

**Authors:** Bin Wang, Chao Xu, Xiaomeng Zhao, Linke Ouyang, Fan Wu, Zhiyuan Zhao, Rui Xu, Kaiwen Liu, Yuan Qu, Fukai Shang, Bo Zhang, Liqun Wei, Zhihao Sui, Wei Li, Botian Shi, Yu Qiao, Dahua Lin, Conghui He  
**arXiv:** [2409.18839](https://arxiv.org/abs/2409.18839)  
**Date:** 2024-09-27  
**Summary page:** https://www.summarizepaper.com/en/paper/2409.18839v1/

## Key points

- MinerU is an open-source solution developed by a team of authors including Bin Wang, Chao Xu, Xiaomeng Zhao, Linke Ouyang, Fan Wu, Zhiyuan Zhao, Rui Xu, Kaiwen Liu, Yuan Qu, Fukai Shang, Bo Zhang, Liqun Wei,
- Zhihao Sui, Wei Li,Botian Shi,Yu Qiao,Dahua Lin,and Conghui He.
- The project addresses challenges in document content analysis within computer vision research.
- Existing open-source solutions struggle to maintain consistency due to diverse document types and content.
- MinerU leverages sophisticated PDF-Extract-Kit models for effective content extraction from various documents.
- It incorporates finely-tuned preprocessing and postprocessing rules for accurate information extraction.
- Experimental results show consistent high performance across different document types with enhanced precision.
- MinerU significantly improves the quality and consistency of results in content extraction.
- The technical report emphasizes MinerU as an open-source solution for precise document content extraction.
- The project is available on GitHub at https://github.com/opendatalab/MinerU.

## Summary

MinerU is an open-source solution developed by a team of authors including Bin Wang, Chao Xu, Xiaomeng Zhao, Linke Ouyang, Fan Wu, Zhiyuan Zhao, Rui Xu, Kaiwen Liu, Yuan Qu, Fukai Shang, Bo Zhang, Liqun Wei,
Zhihao Sui, Wei Li,Botian Shi,Yu Qiao,Dahua Lin,and Conghui He. The project addresses the challenges faced in document content analysis within computer vision research. Despite advancements in technologies like OCR and layout detection for extracting content from documents accurately,
existing open-source solutions often struggle to maintain consistency due to the diverse nature of document types and content. MinerU leverages sophisticated PDF-Extract-Kit models to effectively extract content from various types of documents. It incorporates finely-tuned preprocessing and postprocessing rules to ensure the accuracy of the extracted information. Through experimental results,
MinerU has demonstrated consistent high performance across different document types. This enhanced precision in content extraction significantly improves the quality and consistency of results. The technical report on MinerU emphasizes its capabilities as an open-source solution for precise document content extraction. The project is available on GitHub at https://github.com/opendatalab/MinerU. By providing a reliable tool for extracting content from diverse documents with high precision and consistency,
MinerU contributes to advancing research in computer vision and document analysis fields.