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<!DOCTYPE html>
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<head>
<meta charset="utf-8">
<meta name="description" content="A Large-scale Knowledge Repository for Understanding Hand-Object Interaction">
<meta name="keywords" content="Hand-Object Interaction, Dataset">
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<title>OakInk Dataset CVPR2022 | 手物交互数据库</title>
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Related Projects
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<a class="navbar-item" href="https://kailinli.github.io/SemGrasp">
SemGrasp: Language guided grasp generation (ECCV24)
</a>
<a class="navbar-item" href="https://oakink.net/v2">
OakInk2 (CVPR2024)
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<a class="navbar-item" href="#">
CHORD: Category-level object recovery (ICCV23)
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POEM: Multiview mesh recovery (CVPR23)
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OakInk-HMR
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OakInk-Grasp-Generation
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<h1 class="post-title">
<img class="left" src="img/oakinklogo.png" width="280px" height="auto" alt="OakInk_logo.png">
</h1><br />
<h1 class="title is-1 publication-title">OakInk: A Large-scale Knowledge Repository for Understanding
Hand-Object Interaction</h1>
<div class="is-size-5 publication-authors">
<span class="author-block">
<a href="https://lixiny.github.io">Lixin Yang</a><sup>1,2,*</sup>,</span>
<span class="author-block">
<a href="https://kailinli.top/">Kailin Li</a><sup>1,*</sup>,</span>
<span class="author-block">
<a href="https://scholar.google.com/citations?user=WurpqEMAAAAJ&hl=en">Xinyu
Zhan</a><sup>1,*</sup>,
</span>
<span class="author-block">
<a href="#">Fei Wu</a><sup>1</sup>,
</span>
<span class="author-block">
<a href="https://anran-xu.github.io">Anran Xu</a><sup>1</sup>,
</span>
<span class="author-block">
<a href="https://scholar.google.com/citations?user=-_aPWUIAAAAJ&hl=en">Liu Liu</a><sup>1</sup>,
</span>
<span class="author-block">
<a href="http://mvig.org">Cewu Lu</a><sup>1,2,✉</sup>
</span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block"><sup>1</sup>Shanghai Jiao Tong University,</span>
<span class="author-block"><sup>2</sup>Shanghai Qi Zhi Institute</span>
</div>
* Equal contribution ✉ Corresponding author
<div style="font-size:30px; font-weight: bold;">
CVPR 2022
</div>
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<div class="publication-links">
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<a href="https://openaccess.thecvf.com/content/CVPR2022/html/Yang_OakInk_A_Large-Scale_Knowledge_Repository_for_Understanding_Hand-Object_Interaction_CVPR_2022_paper.html"
class="external-link button is-normal is-rounded is-dark">
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<span>Paper</span>
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<span>arXiv</span>
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<section class="hero teaser">
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<img id="teaser" src="img/teaser.png" class="img-responsive" alt="overview" width="100%" />
<h2 class="subtitle has-text-centered">
OakInk consists of 1) <strong>OakBase</strong> of object affordance and 2) <strong>InkBase</strong> of hand's
interaction.
</h2>
</div>
</div>
</section>
<section class="section">
<div class="container is-max-desktop">
<div class="column is-full-width">
<h3 class="title is-3">Update</h3>
<ul>
<li>
<b><tt>Jun,19,2024</tt></b>:   <a href="https://oakink.net/v2">OakInk2 @ CVPR2024</a> is released !
</li>
<li>
<b><tt>Apr,04,2024</tt></b>:   OakInk could be easily cloned from Huggingface/Dataset at <a
href="https://huggingface.co/datasets/oakink/OakInk-v1">OakInk-v1</a>
</li>
<li>
<b><tt>Dec,11,2023</tt></b>:   <a href="https://github.com/oakink/OakInk-Grasp-Generation">
<strong>Grasp Generation
</strong></a> models on OakInk-Shape are released!
</li>
<li>
<b><tt>Feb,11,2023</tt></b>:   <b>OakBase</b> is released!
</li>
<li>
<b><tt>Jan,03,2023</tt></b>:   <a href="https://github.com/oakink/OakInk-HMR"> <strong>Hand
Mesh Recovery
</strong></a> models on OakInk-Image are released!
</li>
<li> <b><tt>Oct,18,2022</tt></b>:   OakInk <b>public v2.1</b> is released! <br />
<script src="https://ajax.googleapis.com/ajax/libs/jquery/2.1.1/jquery.min.js"></script>
<details>
<summary>expand to see details</summary>
Within this update, several artifacts have been fixed, including: wrong poses, time delay, and contact
surface mismatches;
<b>NOTE</b>:
If you downloaded the OakInk dataset before <u>11:00 AM October 18, 2022, UTC</u>,
You <b>only</b> need to replace the previous anno.zip by this newly released: <a
href="https://forms.gle/g6QEmmCeZYLGaVe29" target="_blank"><span class="icon"> <i
class="fas fa-download"></i>
</span>anno_v2.1.zip</a> <i style="color:gray;">(access via Google Forms)</i>,
unzip it and keep the same file structures as before, and install the latest
<a href="https://github.com/lixiny/OakInk"> <b>OakInk Toolkit</b></a>.
</details>
</li>
<li>
<b><tt>Jul,26,2022</tt></b>:   <a href="https://github.com/KailinLi/Tink"> <strong>Tink
</strong></a> has been made public.
</li>
<li>
<b><tt>Jun,28,2022</tt></b>:   OakInk <b>public v2</b> & <a href="https://github.com/lixiny/OakInk">
<b>OakInk Toolkit</b></a> -- a Python dataloader, are released!
</li>
<li>
<b><tt>Mar,03,2022</tt></b>:   OakInk
got accepted by <a href="https://cvpr2022.thecvf.com"><strong>CVPR 2022</strong></a>.
</li>
</ul>
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<section class="section">
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<h3 class="title is-3">About</h3>
<div class="content has-text-justified">
OakInk contains three datasets:<br />
<ul>
<li>
<b>OakBase</b>: Object Affordance Knowledge (Oak) base, including objects' part-level segmentation and
attributes.
</li>
<li>
<b>OakInk-Image</b>: a video dataset with 3D hand-object pose and shape annotations.
</li>
<li>
<b>OakInk-Shape</b>: a 3D grasping pose dataset with hand and object mesh models.
</li>
</ul>
The OakInk-Image contains 230K image frames that capture a total of 12 subjects performing
up to 5 intent-oriented interactions with 100 objects from 32 categories.
The object poses were captured from a MoCap system, while the MANO hand poses are fitted from 2D keypoint
annotation.
Based on the hand-object poses from real-world human demonstrations,
we transfer the hand pose on the real-world object to the virtual objects with similar affordances through a
interaction transfer module: Tink.
All the real-world and transferred interactions constitute the geometry-based dataset: OakInk-Shape.
The OakInk-Shape contains 50K different hand-object poses and models.
</p>
</div>
</div>
</section>
<section class="section">
<div class="container is-max-desktop">
<h3 class="title is-3">Download</h3>
<div id="oakbase-div" class="content has-text-justified">
<h4 class="title is-4">OakInk</h4>
Download at: <a href="https://huggingface.co/datasets/oakink/OakInk-v1" target="_blank"><span class="icon">
<i class="fas fa-download"></i> </span>Hugging Face</a>.
<br>
For researchers in China, you can download OakInk from the alternative mirror:
<a href="https://pan.baidu.com/s/1H2hW1ZXEbNccOUzYX9cPkA" target="_blank"><span class="icon"> <i
class="fas fa-download"></i>
</span>百度云盘</a> (hrt9)
<br>
</div>
After download all the files, you need to complete the <a href="https://forms.gle/g6QEmmCeZYLGaVe29"
target="_blank"><span class="icon"> <i class="fas fa-file-alt"></i>
</span>Google Form</a> to get the annotation file.
<br>
Arrange all zip files into the directory, eg.<code>$OAKINK_DIR/zipped</code> as follow
<br>
<pre><code>$OAKINK_DIR/zipped
├── OakBase.zip
├── image
│ ├── anno_v2.1.zip # access via Google Forms
│ ├── obj.zip
│ └── stream_zipped
│ ├── oakink_image_v2.z01
│ ├── ...
│ ├── oakink_image_v2.z10
│ └── oakink_image_v2.zip
└── shape
├── metaV2.zip
├── OakInkObjectsV2.zip
├── oakink_shape_v2.zip
└── OakInkVirtualObjectsV2.zip</code></pre>
and follow the <a href="https://github.com/oakink/OakInk/blob/main/docs/datasets.md#download-full-oakink"
target="_blank"><span class="icon"> <i class="fab fa-github"></i>
</span>instruction</a> to verify checksums and unzip the files.
</section>
<section class="section">
<div class="container is-max-desktop content">
<h3 class="title is-3">Resources</h3>
Details of dataset annotations, please refer to <a
href="https://github.com/oakink/OakInk/blob/main/docs/datasets.md#data-documentation" target="_blank"><span
class="icon"> <i class="fab fa-github"></i></span>Data documentation</a>.
<br>
Details of dataset splits for various tasks, please refer to <a
href="https://github.com/oakink/OakInk/blob/main/docs/datasets.md#data-splitting" target="_blank"><span
class="icon"> <i class="fab fa-github"></i></span>Data splitting</a>.
<br>
Load OakBase and visualize object parts and attributes, please refer to <a
href="https://github.com/oakink/OakInk/blob/main/scripts/demo_oak_base.py" target="_blank"><span class="icon">
<i class="fab fa-github"></i></span>demo_oak_base.py</a>.
<br>
Load OakInk-Image and OakInk-Shape for visualization, please refer to <a
href="https://github.com/oakink/OakInk#load-and-visualize" target="_blank"><span class="icon"> <i
class="fab fa-github"></i></span>Load and visualize</a>.
<br>
Train hand mesh recovery models on OakInk-Image, please refer to <a href="https://github.com/oakink/OakInk-HMR"
target="_blank"><span class="icon"> <i class="fab fa-github"></i></span>OakInk-HMR</a>.
<br>
Train grasp generation models on OakInk-Shape, please refer to <a
href="https://github.com/oakink/OakInk-Grasp-Generation" target="_blank"><span class="icon"> <i
class="fab fa-github"></i></span>OakInk-Grasp-Generation</a>.
</div>
</section>
<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h3 class="title is-3">BibTeX</h3>
<pre><code>@InProceedings{YangCVPR2022OakInk,
author = {Yang, Lixin and Li, Kailin and Zhan, Xinyu and Wu, Fei and Xu, Anran and Liu, Liu and Lu, Cewu},
title = {{OakInk}: A Large-Scale Knowledge Repository for Understanding Hand-Object Interaction},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2022},
}</code></pre>
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