TableVerse-5K

A Table-Parsing Benchmark for the StrucTab Framework

GitHub Repo • ModelScope Dataset • Arxiv Paper

News

• [2026.06] 📖 Code and the TableVerse-5K benchmark are released!
• [2026.06] 🎉 Our StrucTab is accepted by ECCV 2026!

Overview

TableVerse-5K is the evaluation benchmark for StrucTab, a structured optimization framework for table parsing, the task of converting a table image into structured HTML. Each sample pairs a table image with an instruction prompt and a ground-truth HTML table, and models are scored with the TEDS / TEDS-S metrics.

The benchmark pipeline is illustrated below:

Contents

• Statistics
• Dataset Structure
• Data Format
• Usage
• Citation
• License

Statistics

Item	Details
Samples	5K table images
Task	Table parsing (image → HTML table)
Languages	Bilingual (Chinese and English table content)
Output format	HTML (<table>...</table>)
Scoring metrics	TEDS, TEDS-S

Dataset Structure

data/
├── TableVerse_5K.jsonl     # annotations for all samples
└── images/                 # table images (*.jpg)

Data Format

Each line of TableVerse_5K.jsonl is a JSON object:

{
  "image_path": "images/xxx.jpg",
  "question": "You are an AI specialized in recognizing and extracting table from images...",
  "ref_answer": "<table>...</table>"
}

Field	Type	Description
image_path	string	Relative path from data/; also serves as the unique sample key
question	string	The instruction / prompt fed to the model together with the image
ref_answer	string	Ground-truth table in HTML (<table>...</table>)

Usage

Please refer to the GitHub repository for the full inference and evaluation scripts.

# 1. Clone the code repository
git clone https://github.com/VirtualLUOUCAS/StrucTab
cd StrucTab/benchmark
pip install -r requirements.txt

# 2. Clone this dataset and place its contents under benchmark/data/
#    so that you have benchmark/data/TableVerse_5K.jsonl and benchmark/data/images/

# 3. Inference
python infer.py --api_type openai_compat --model_name <model> --base_url <url>

# 4. Score (requires the TEDS judging service, see the repo README)
python judge.py

Citation

If you find TableVerse-5K useful, please consider citing (placeholder; to be updated):

@inproceedings{StrucTab_2026,
  title     = {{StrucTab}: A Structured Optimization Framework for Table Parsing},
  author    = {Li, Gengluo and Peng, Shangpin and Zhang, Chengquan and Wu, Binghong and Feng, Hao and Wang, Weinong and Lyu, Pengyuan and Shen, Huawen and Wan, Xingyu and Tian, Zhuotao and others},
  booktitle = {Proceedings of the European Conference on Computer Vision},
  pages     = {672--690},
  year      = {2026}
}

License

This dataset is released for research purposes only.