---
license: mit
task_categories:
- object-detection
- visual-document-retrieval
language:
- en
- fr
tags:
- table
- extraction
- detection
- structure
- recognition
pretty_name: Table Extraction Scientific Datasets
size_categories:
- 10K<n<100K
---

<div align="center" xmlns="http://www.w3.org/1999/html">
<h1 align="center">
Benchmarking Table Extraction from Heterogeneous Scientific PDF Documents
</h1>
<a href="https://gitlab.inria.fr/msoric/table-extraction-benchmark/-/blob/main/docs/main.pdf?ref_type=heads">
    <img src="https://img.shields.io/badge/Preprint-Benchmark%20Table%20Extraction-b31b1b.svg?logo=arXiv" alt="Preprint">
</a>
<a href="https://gitlab.inria.fr/msoric/table-extraction-benchmark">
    <img src="https://img.shields.io/badge/GitLab-black?logo=gitlab&link=https%3A%2F%2Fgitlab.inria.fr%2Fmsoric%2Ftable-extraction-benchmarkds" alt="GitLab">
</a>
<a href="https://huggingface.co/datasets/marijanic/table-extraction-scientific-datasets">
    <img src="https://img.shields.io/badge/Hugging%20Face-Dataset-yellow?logo=hugging%20face&link=https%3A%2F%2Fhuggingface.co%2Fdatasets%2Fmarijanic%2Ftable-extraction-scientific-datasets" alt="Hugging Face Dataset">
</a>
<a href="https://dataset-tab.s3.eu-west-3.amazonaws.com/brgm/images/crgeos20211464151_v1_4.jpg">
    <img src="https://img.shields.io/badge/AWS-S3%20Bucket-%23ff9900?labelColor=black&link=https%3A%2F%2Fdataset-tab.s3.eu-west-3.amazonaws.com%2Fbrgm%2Fimages%2Fcrgeos20211464151_v1_4.jpg" alt="AWS S3 Bucket">
</a>
</div>

## Dataset Sources

- **Repository:** [GitLab](https://gitlab.inria.fr/msoric/table-extraction-benchmark)

## Dataset Details 


- PubTables
  - Subset of PubTables-Test dataset, enriched with HTML table ground truth
  - `/images`: 42,942 JPG files; one file for each page image
  - `/test`: 42,942 XML files containing bounding boxes in PASCAL VOC format
  - `/pdfs`: 23,567 PDF files from which images are taken from
  - `/html`: 55,991 HTML files containing extracted tables with in HTML mark-up
  - `/word`: 46,942 JSON files containing bounding boxes of tokens in images 

- Table-arXiv
  - Dataset synthetically generated from LaTeX source files from arXiv preprints for ground truth generation.
  - `/images`: 36,869 JPG files; one file for each page image
  - `/test`: 5,327 XML files containing bounding boxes in PASCAL VOC format
  - `/pdfs`: 2,488 PDF files from which images are taken from
  - `/html`: 6,441 HTML files containing extracted tables with in HTML mark-up
  - `/word`: 40,261 JSON files containing bounding boxes of tokens in images

- Table-BRGM
  - Dataset manually annotated, domain-specific and comprises French and English geological reports sourced from a selection of BRGM
  - `/images`: 2003 JPG files; one file for each page image
  - `/test`: 251 XML files containing bounding boxes in PASCAL VOC format
  - `/pdfs`: 26 PDF files from which images are taken from
  - `/html`: 346 HTML files containing extracted tables with in HTML mark-up
  - `/word`: 2003 JSON files containing bounding boxes of tokens in images

- ICDAR-2013
  - Dataset manually corrected from the ICDAR-2013 competition, contains European Union and US Government PDF reports.
  - `/images`: 238 JPG files; one file for each page image
  - `/test`: 135 XML files containing bounding boxes in PASCAL VOC format
  - `/pdfs`: 67 PDF files from which images are taken from
  - `/html`: 163 HTML files containing extracted tables with in HTML mark-up
  - `/word`: 238 JSON files containing bounding boxes of tokens in images

## Dataset Creation
For Table-arXiv, we provide the code to generate de dataset (input images and GT annotations) from .tex source code in [Repo](https://gitlab.inria.fr/msoric/table-transformer). We did not include the dataset used because of the license:  
[arXiv.org - Non-exclusive license to distribute](https://arxiv.org/licenses/assumed-1991-2003/license.html).

## Citation
@misc{soric2025benchmarkingtableextractionheterogeneous,
      title={Benchmarking Table Extraction from Heterogeneous Scientific Extraction Documents}, 
      author={Marijan Soric and Cécile Gracianne and Ioana Manolescu and Pierre Senellart},
      year={2025},
      eprint={2511.16134},
      archivePrefix={arXiv},
      primaryClass={cs.DB},
      url={https://arxiv.org/abs/2511.16134}, 
}