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<!doctype html>
<html lang="en">
<head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<!-- Global site tag (gtag.js) - Google Analytics -->
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<script>
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<title>Jun CEN • 岑俊</title>
<meta name="author" content="Jun CEN">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="This is the academic homepage of Jun CEN">
<link rel="stylesheet" type="text/css" href="stylesheet.css">
<link rel="icon" type="image/png" href="images/leon.png">
<!-- Make all the links contained on this page to be opened with a new page. -->
<base target="_blank" />
</head>
<body>
<table style="width:100%;max-width:800px;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr style="padding:0px">
<td style="padding:0px">
<!-- ########## About ME ########## -->
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr style="padding:0px">
<td style="padding:2.5%;width:63%;vertical-align:middle">
<p style="text-align:center">
<name>Jun CEN</name>
</p>
<p>
I am a Ph.D. student at the
<a href="http://ri.ust.hk">Robotics Institute</a>, <a href="https://www.ust.hk">The Hong Kong University of Science and Technology</a>,
where I work on computer vision and autonomous driving under the supervision of <a href="https://cqf.io/">Prof. Qifeng Chen</a> and <a href="https://research.monash.edu/en/persons/michael-wang-2">Prof. Michael Yu Wang</a>. Now I work as a Research Intern at <a href="https://damo.alibaba.com/">DAMO Academy, Alibaba Group</a>.
</p>
<p>
I got my MSc degree of Mechanical Engineering in HKUST between 2019-2020. At the mean time, I worked as a Research Assistant in <a href="https://crai.cuhk.edu.cn/"> Robotics and Artificial Intelligence Laboratory, CUHK(SZ).</a>
Before that, I graduated from
<a href="https://www.zju.edu.cn/">Zhejiang University</a>
in 2019 with a bachelor's degree in Mechatronics.
</p>
<p style="text-align:center">
<a href="mailto:jcenaa@connect.ust.hk">Email</a>  / 
<a href="https://scholar.google.com/citations?user=7SKAhBwAAAAJ&hl=en">Google Scholar</a>  / 
<a href="https://github.com/Jun-CEN">Github</a> / 
<a href="work/Resume_Jun_CEN.pdf">CV</a>
</p>
</td>
<td style="padding:2.5%;width:40%;max-width:40%">
<a href="images/myself.jpg" title="Hi! I'm Haoran">
<img style="width:100%;max-width:100%" alt="profile photo" src="images/myself.jpg" class="hoverZoomLink">
</a>
</td>
</tr>
</tbody></table>
<!-- ########## Section: Research Intersets ########## -->
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr>
<td style="padding:20px;width:100%;vertical-align:middle">
<heading>Research</heading>
<p>
My research lies in open-world perception systems of autonomous driving, including open-world semantic segmentation, 3D object detection, and 3D semantic segmentation, as well as distributed learning including federated learning and blockchain.
<!-- Representative papers are <span class="highlight">highlighted</span>. -->
</p>
</td>
</tr>
</tbody></table>
<!-- ########## Section: Research Works ########## -->
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<!-- ##### ECCV 2022 #####-->
<tr>
<td style="padding:15px;width:25%;vertical-align:middle">
<img src="images/eccv2022.png" style="max-width:100%" alt="PiP architecture">
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<img style="width: 35px" src="images/new.png">
<a href="prime/">
<papertitle>Open-world Semantic Segmentation for LIDAR Point Clouds</papertitle>
</a>
<br />
<strong>Jun Cen</strong>, Peng Yun, Shiwei Zhang, Junhao Cai, Di Luan, Michael Yu Wang, Ming Liu, Mingqian Tang
<br />
<br />
<em>European Conference on Computer Vision <strong>(ECCV 2022)</strong></em>, Tel Aviv, Israel.
<br />
<p>
<q>We propose the open-world semantic segmentation system in 3D LIDAR Point Cloud domain and use redundancy classifiers to solve the problem.</q>
</p>
<a href="https://arxiv.org/abs/2207.01452">arxiv</a>  / 
<a href="https://github.com/Jun-CEN/Open_world_3D_semantic_segmentation">code</a>  / 
</td>
</tr>
<!-- ##### 3DV 2021 #####-->
<tr>
<td style="padding:15px;width:25%;vertical-align:middle">
<img src="images/3dv_2021.png" style="max-width:100%" alt="PiP architecture">
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="prime/">
<papertitle>Open-set 3D Object Detection</papertitle>
</a>
<br />
<strong>Jun Cen</strong>, Peng Yun, Junhao Cai, Michael Yu Wang, Ming Liu
<br />
<br />
<em>International Conference on 3D Vision <strong>(3DV 2021)</strong></em>, London, UK.
<br />
<p>
<q>We propose the open-set 3D object detector to detect both known objects as well as unknonw objects.</q>
</p>
<a href="https://arxiv.org/abs/2112.01135">arXiv</a>
</td>
</tr>
<!-- ##### ICCV 2021 #####-->
<tr>
<td style="padding:15px;width:25%;vertical-align:middle">
<img src="images/head_3.jpg" style="max-width:100%" alt="PiP architecture">
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="prime/">
<papertitle>Deep Metric Learning for Open World Semantic Segmentation</papertitle>
</a>
<br />
<strong>Jun Cen</strong>, Peng Yun, Junhao Cai, Michael Yu Wang, Ming Liu
<br />
<br />
<em>International Conference on Computer Vision <strong>(ICCV 2021)</strong></em>, Montreal, Canada.
<br />
<p>
<q>Open-set segmentation detects unknown objects, then few-shot incremental learning is adopted to involve unknown objects into the knowledge base of the neural network.</q>
</p>
<a href="https://arxiv.org/abs/2108.04562">arXiv</a>  / 
<a href="https://github.com/Jun-CEN/Open-World-Semantic-Segmentation">code</a>  / 
<a href="https://youtu.be/t1vl7MzGb2Q"> video </a>
<!-- <span class="unavailable">code (to be released)</span> -->
</td>
</tr>
<!-- ##### IROS 2021 #####-->
<tr>
<td style="padding:15px;width:25%;vertical-align:middle">
<img src="images/iros2021.png" style="max-width:100%" alt="PiP architecture">
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="planning-informed-prediction/">
<papertitle>BORM: Bayesian Object Relation Model for Indoor Scene Recognition</papertitle>
</a>
<br />
Liguang Zhou, <strong>Jun Cen</strong>, Xingchao Wang, Zhenglong Sun, Tin Lun Lam, Yangsheng Xu
<br />
<br />
<em>International Conference on Intelligent Robots and Systems <strong>(IROS 2021)</strong></em>, Prague, Czech Republic.
<br />
<p>
<q>Improve the scene classification accuracy through considering discriminative object pairs.</q>
</p>
<a href="https://arxiv.org/abs/2108.00397">arXiv</a>  / 
<a href="https://github.com/Jun-CEN/BORM">code</a>  / 
<a href="https://www.youtube.com/watch?v=8lHP-sdNRJ8"> video
</td>
</tr>
</tbody></table>
<!-- ########## Section: Service ########## -->
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20"><tbody>
<tr>
<td>
<heading>Service</heading>
</td>
</tr>
</tbody></table>
<table width="100%" align="center" border="0" cellpadding="20"><tbody>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img src="images/ieee_ras_logo.png" style="max-width:100%">
</td>
<td width="75%" valign="center">
Reviewer for IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
</td>
</tr>
</tbody></table>
<!-- ########## Tools: Visitor Locations Visualization ########## -->
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<!-- ########## Last: Acknowledgment ########## -->
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr>
<td style="padding:0px">
<p style="text-align:right;font-size:small;">
Made from
<a href="https://jonbarron.info/">Dr. Jon Barron</a>'s website design.
</p>
</td>
</tr>
</tbody></table>
</td>
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</body>
</html>