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<!DOCTYPE html>
<!-- saved from url=(0041)https://www.cs.cmu.edu/~aharley/rvl-cdip/ -->
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=windows-1252">
<style>
td,
th {
background: #f0f0f0;
text-align: center;
}
#labels {
width: 100%;
overflow: hidden;
text-overflow: ellipsis;
height: 1.5em;
z-index: 5;
}
.label {
float: left;
width: 12.5%;
overflow: hidden;
text-overflow: ellipsis;
white-space: nowrap;
}
.twoline {
line-height: 1em;
margin-top: -0.75em;
padding-bottom: 0.5em;
}
.trt{
font-size: 10%;
line-height: 15px;
}
</style>
<link href="./TableBank Dataset_files/projectPage.css" rel="stylesheet" type="text/css">
<script async="" src="./TableBank Dataset_files/analytics.js"></script>
<script async="" src="./TableBank Dataset_files/analytics.js"></script>
<script type="text/javascript" src="./TableBank Dataset_files/jquery-1.11.1.min.js"></script>
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<script async src="https://www.googletagmanager.com/gtag/js?id=UA-131758570-3"></script>
<script>
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gtag('js', new Date());
gtag('config', 'UA-131758570-3');
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<link href="./TableBank Dataset_files/css" rel="stylesheet" type="text/css">
<title>TableBank Dataset</title>
</head>
<body>
<div id="container">
<div id="page">
<div id="pageContent">
<h1>The TableBank Dataset</h1>
<!-- <p>Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou, Zhoujun Li</p> -->
<p>TableBank is a new image-based table detection and recognition dataset built with novel weak
supervision from Word and Latex documents on the internet, contains 417K high-quality labeled
tables.
</p>
<p>Here are Example annotations of the TableBank. </p>
<h4>Table Detection Task</h4>
<table>
<tr>
<td>
<a><img src="./sample_imgs/001.png" style="width:100%; height:auto; max-width:3540px; "></a>
</td>
<td>
<a><img src="./sample_imgs/002.png" style="width:100%; height:auto; max-width:3540px; "></a>
</td>
<td>
<a><img src="./sample_imgs/003.png" style="width:100%; height:auto; max-width:3540px; "></a>
</td>
<td>
<a><img src="./sample_imgs/004.png" style="width:100%; height:auto; max-width:3540px; "></a>
</td>
<td>
<a><img src="./sample_imgs/005.png" style="width:100%; height:auto; max-width:3540px; "></a>
</td>
<td>
<a><img src="./sample_imgs/006.png" style="width:100%; height:auto; max-width:3540px; "></a>
</td>
<td>
<a><img src="./sample_imgs/007.png" style="width:100%; height:auto; max-width:3540px; "></a>
</td>
<td>
<a><img src="./sample_imgs/008.png" style="width:100%; height:auto; max-width:3540px; "></a>
</td>
</tr>
</table>
<p> A new benchmark dataset DocBank (<a href="https://github.com/doc-analysis/DocBank">repo</a>, <a
href="https://arxiv.org/abs/2006.01038">paper</a>) is now available for document layout
analysis. <br>
Our paper has been accepted in <a
href="https://lrec2020.lrec-conf.org/en/conference-programme/accepted-papers/">LREC 2020</a>. <br>
For more details, please refer to our GitHub page: <a href="https://github.com/doc-analysis/TableBank">https://github.com/doc-analysis/TableBank</a>.
</p>
<h2>Statistics on Train/Val/Test sets</h2>
<h3>Table Detection</h3>
<table>
<thead>
<tr>
<th>Source</th>
<th>Train</th>
<th>Val</th>
<th>Test</th>
</tr>
</thead>
<tbody>
<tr>
<td>Latex</td>
<td>187199</td>
<td>7265</td>
<td>5719</td>
</tr>
<tr>
<td>Word</td>
<td>73383</td>
<td>2735</td>
<td>2281</td>
</tr>
<tr>
<td>Total</td>
<td>260582</td>
<td>10000</td>
<td>8000</td>
</tr>
</tbody>
</table>
<h3>Table Structure Recognition</h3>
<table>
<thead>
<tr>
<th>Source</th>
<th>Train</th>
<th>Val</th>
<th>Test</th>
</tr>
</thead>
<tbody>
<tr>
<td>Latex</td>
<td>79486</td>
<td>6075</td>
<td>3036</td>
</tr>
<tr>
<td>Word</td>
<td>50977</td>
<td>3925</td>
<td>1964</td>
</tr>
<tr>
<td>Total</td>
<td>130463</td>
<td>10000</td>
<td>5000</td>
</tr>
</tbody>
</table>
<h2>Download</h2>
In order to reduce the loss caused by download interruption, we divided "TableBank.zip" into 5 parts, and after downloading all of them, use the decompression software to decompress them together.
<table width="100%">
<tbody>
<tr>
<th>File</th>
<th>Size</th>
<th>md5sum</th>
</tr>
<tr>
<td>TableBank.zip
<br>[<a href="https://layoutlm.blob.core.windows.net/tablebank/dataset/TableBank.zip.001?sv=2022-11-02&ss=b&srt=o&sp=r&se=2033-06-08T16:48:15Z&st=2023-06-08T08:48:15Z&spr=https&sig=a9VXrihTzbWyVfaIDlIT1Z0FoR1073VB0RLQUMuudD4%3D" onclick="trace_page('download TableBank');">1</a>]
[<a href="https://layoutlm.blob.core.windows.net/tablebank/dataset/TableBank.zip.002?sv=2022-11-02&ss=b&srt=o&sp=r&se=2033-06-08T16:48:15Z&st=2023-06-08T08:48:15Z&spr=https&sig=a9VXrihTzbWyVfaIDlIT1Z0FoR1073VB0RLQUMuudD4%3D">2</a>]
[<a href="https://layoutlm.blob.core.windows.net/tablebank/dataset/TableBank.zip.003?sv=2022-11-02&ss=b&srt=o&sp=r&se=2033-06-08T16:48:15Z&st=2023-06-08T08:48:15Z&spr=https&sig=a9VXrihTzbWyVfaIDlIT1Z0FoR1073VB0RLQUMuudD4%3D">3</a>]
[<a href="https://layoutlm.blob.core.windows.net/tablebank/dataset/TableBank.zip.004?sv=2022-11-02&ss=b&srt=o&sp=r&se=2033-06-08T16:48:15Z&st=2023-06-08T08:48:15Z&spr=https&sig=a9VXrihTzbWyVfaIDlIT1Z0FoR1073VB0RLQUMuudD4%3D">4</a>]
[<a href="https://layoutlm.blob.core.windows.net/tablebank/dataset/TableBank.zip.005?sv=2022-11-02&ss=b&srt=o&sp=r&se=2033-06-08T16:48:15Z&st=2023-06-08T08:48:15Z&spr=https&sig=a9VXrihTzbWyVfaIDlIT1Z0FoR1073VB0RLQUMuudD4%3D">5</a>]
</td>
<td>24,897,840,399B (23.1GB)</td>
<td> - </td>
</tr>
</tbody>
</table>
<h2>Annotation Format
</h2>
<p>The annotation of the Table Detection task uses the format of the MS COCO dataset. For specific
format information, please refer to the website: <a
href="https://cocodataset.org/#format-data">https://cocodataset.org/#format-data</a>.
Besides, our data annotations can be loaded through <a
href="https://github.com/cocodataset/cocoapi">COCO API</a>.
</p>
<p>
The annotation of the Table Recognition task is HTML tag sequences. The tags are <tabular>,
</tabular>, <thead>, </thead>, <tbody>, </tbody>, <tr>, </tr>, <td>,
</td>, <tdy>, <tdn>.
</p>
<h2>Citation</h2>
<p>If you use this dataset, please cite our <a href="https://arxiv.org/abs/1903.01949">paper</a>:
</p>
<div class="cite">
<p>TableBank: A Benchmark Dataset for Table Detection and Recognition</p>
<p>Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou, Zhoujun Li</p>
</div>
<p>Bibtex format:</p>
<div class="cite">
<code>
@misc{li2019tablebank,<br>
title={TableBank: A Benchmark Dataset for Table Detection and Recognition},<br>
author={Minghao Li and Lei Cui and Shaohan Huang and Furu Wei and Ming Zhou and Zhoujun Li},<br>
year={2019},<br>
eprint={1903.01949},<br>
archivePrefix={arXiv},<br>
primaryClass={cs.CV}<br>
}
</code>
</div>
</div>
</div>
</div>
</body>
</html>