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This is the homepage of Jingwen Ye. |
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<!DOCTYPE HTML> | ||
<html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> | ||
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<title>Jingwen Ye</title> | ||
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<meta name="author" content="Jingwen Ye"> | ||
<meta name="viewport" content="width=device-width, initial-scale=1"> | ||
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<link rel="stylesheet" type="text/css" href="stylesheet.css"> | ||
<link rel="icon" type="image/png" href="jingwen.jpg"> | ||
</head> | ||
<!-- | ||
<div style="position: relative; right: 370px; text-align:right;"> | ||
<small><em><q>It's about a man who has nothing, who risks everything, to feel something.</q> --Jessica Day</em></small> | ||
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<p style="text-align:center"> | ||
<name>叶静雯 (Jingwen Ye)</name> | ||
</p> | ||
<p> | ||
Welcome to my homepage! I'm Jingwen Ye, | ||
currently a research fellowship at <a href=http://www.lv-nus.org//>Learning and Vision Lab</a>, National University of Singapore, | ||
working with <a href=https://sites.google.com/site/sitexinchaowang/>Prof. Xinchao Wang</a>. | ||
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I received my PhD from Zhejiang University, studying computer vision under <a href="https://vipazoo.cn/people/songmingli.html">Prof. Mingli Song</a> and <a href="https://person.zju.edu.cn/chenc">Chun Chen</a>. Prior to that, I got my B. Eng. Degree from Dalian University of Technology. | ||
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</p> | ||
<p> | ||
My current research interests are mainly about <strong>Privacy-aware Transfer Learning</strong> and <strong>Effective Model Reusing</strong>. Specially, I focus on the privacy issues on the AIGC models. Also I investigate deeper with knowledge distillation and amalgamation techniques to improve the performance of the multi-task networks. | ||
</p> | ||
<p style="text-align:center"> | ||
<a href="mailto:[email protected]">Email</a>  /  | ||
<a href="Jingwen_Ye_NUS.pdf">CV</a>  /  | ||
<a href="https://scholar.google.com/citations?user=8GQnNP0AAAAJ&hl">Google Scholar</a>  /  | ||
<a href="https://github.com/JngwenYe">Github</a>  /  | ||
<a href="https://twitter.com/petrina_yee?s=21">Twitter</a>  /  | ||
<a href="http://linkedin.com/in/jingweny0520">Linkedin</a> | ||
</p> | ||
<small><em><q>The world is full of magic things, patiently waiting for our senses to grow sharper. </q> -- W.B. Yeats</em></small> | ||
</td> | ||
<td style="padding:2.5%;width:40%;max-width:40%"> | ||
<a href="jingwen.jpg"><img style="width:100%;max-width:100%" alt="profile photo" src="jingwen.jpg" class="hoverZoomLink"></a> | ||
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<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20"><tbody> | ||
<tbody><tr> | ||
<td width="100%" valign="middle"> | ||
<heading>Selected Publications</heading> | ||
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style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"> | ||
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<div><img style="width:100%;max-width:100%" src="data/cloning.png"></div> | ||
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<td style="padding:30px;width:60%;vertical-align:middle"> | ||
<papertitle>Partial Network Cloning | ||
</papertitle> | ||
<br> | ||
<br> | ||
<strong>Jingwen Ye</strong>, | ||
<a href="http://121.37.94.87/">Songhua Liu</a>, | ||
<a href="https://sites.google.com/site/sitexinchaowang/">Xinchao Wang</a> | ||
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<br> | ||
IEEE Conference on Computer Vision and Pattern Recognition <strong>(CVPR)</strong>, 2023 | ||
<br> | ||
<a href="https://arxiv.org/abs/2303.10597">[paper]</a> | ||
<a href="https://github.com/JngwenYe/PNCloning">[code]</a> | ||
<a href="https://www.youtube.com/watch?v=JV8Ozatq56s">[video]</a> | ||
<a href="https://mp.weixin.qq.com/s/aoaeo6cY2RJ0IwQrIxZMsw">[blog]</a> | ||
<p> | ||
PNC conducts partial parametric "cloning" from a source network and then injects the cloned module to the target, without modifying its parameters. | ||
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<div><img style="width:100%;max-width:100%" src="images/deposit.png"></div> | ||
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<td style="padding:30px;width:60%;vertical-align:middle"> | ||
<papertitle> Learning with Recoverable Forgetting | ||
</papertitle> | ||
<br> | ||
<br> | ||
<strong>Jingwen Ye</strong>, | ||
Yifan Fu, | ||
<a href="https://scholar.google.com/citations?user=4OjO-WYAAAAJ&hl=en">Jie Song</a>, | ||
<a href="https://adamdad.github.io/">Xingyi Yang</a>, | ||
<a href="http://121.37.94.87/">Songhua Liu</a>, | ||
<a href="https://scholar.google.com/citations?user=byaSC-kAAAAJ">Xin Jin</a>, | ||
<a href="https://vipazoo.cn/people/songmingli.html">Mingli Song</a>, | ||
<a href="https://sites.google.com/site/sitexinchaowang/">Xinchao Wang</a> | ||
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<br> | ||
European Conference on Computer Vision<strong>(ECCV)</strong>, 2022 | ||
<br> | ||
<a href="https://arxiv.org/abs/2207.08224">[paper]</a> | ||
<a href="https://github.com/JngwenYe/LIRF">[code]</a> | ||
<a href="https://mp.weixin.qq.com/s/5vin9G4jD3fMQjq_zGOfyw">[blog]</a> | ||
<p> | ||
LIRF explicitly handles the task- or sample-specific knowledge removal and recovery. | ||
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<div><img style="width:100%;max-width:100%" src="images/sdb.png"></div> | ||
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<td style="padding:30px;width:60%;vertical-align:middle"> | ||
<papertitle>Safe Distillation Box | ||
</papertitle> | ||
<br> | ||
<br> | ||
<strong>Jingwen Ye</strong>, | ||
Yining Mao, | ||
<a href="https://scholar.google.com/citations?user=4OjO-WYAAAAJ&hl=en">Jie Song</a>, | ||
<a href="">Cheng Jing</a> | ||
<a href="https://sites.google.com/site/sitexinchaowang/">Xinchao Wang</a> | ||
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<br> | ||
d <strong>(AAAI)</strong>, 2022 | ||
<br> | ||
<a href="https://arxiv.org/abs/2303.10597">[paper]</a> | ||
<a href="https://github.com/JngwenYe/PNCloning">[code]</a> | ||
<a href="https://www.youtube.com/watch?v=JV8Ozatq56s">[video]</a> | ||
<a href="https://mp.weixin.qq.com/s/aoaeo6cY2RJ0IwQrIxZMsw">[blog]</a> | ||
<p> | ||
SDB allows us to wrap a pre-trained model in a virtual box for intellectual property protection. | ||
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<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody> | ||
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<heading>Work Experience</heading> | ||
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<strong> Research Fellow,  National University of Singapore</strong> | ||
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Oct. 2021 -- Present | ||
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<strong> Research Intern,  Alibaba Group</strong> | ||
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Oct. 2017 -- Mar. 2019 | ||
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<strong>Research Intern,&Alibaba-Zhejiang University Joint Institute</strong> | ||
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Jul. 2017 -- Sep. 2021 | ||
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<heading>Education</heading> | ||
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<table table width="100%" align="center" border="0" cellspacing="0" cellpadding="20"><tbody> | ||
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<img src="images/zju.png" width="80"> | ||
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<strong> Ph.D Student,  Zhejiang University</strong>,    (Sep. 2016 -- Jun. 2021) <br> | ||
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College of Computer Science and Technology <br> | ||
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<strong>Outstanding Graduate</strong>,   Advisor: Prof. Chun Chen and Prof. Mingli Song <br> | ||
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<table table width="100%" align="center" border="0" cellspacing="0" cellpadding="20"><tbody> | ||
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<img src="images/dut.png" width="80"> | ||
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<strong>B.Eng.,  Dalian University of Technology</strong>,   (Sep. 2012 -- Jun. 2016) <br> | ||
<br> | ||
School of Information and Communication Engineering | ||
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Outstanding Graduate, <strong>Ranking: 1/35</strong> | ||
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<heading>Awards</heading> | ||
<br> <br> | ||
<em>Best Paper Award of International Conference on Visual Communications and Image Processing (2022)</em> | ||
<br> <br> | ||
<em>Outstanding Graduate of Zhejiang Province (2021)</em> | ||
<br> <br> | ||
<em>National Scholarship (top 2\%); Graduate of Merit/Triple A Graduate (2019 & 2020)</em><br> <br> | ||
<em>Excellent Intern of Alibaba-Zhejiang University Joint Research Institute of Frontier Technologise (2020)</em><br> <br> | ||
<em>Candidate of Zhu Kezhen Scholarship (top 1\%) (2019)</em><br> <br> | ||
<em>Most Valuable Academic Award of Doctoral Forum (2019)</em><br> <br> | ||
<em>Excellent Social Practice Individual Award (2018)</em><br> <br> | ||
<em>Award of Honor for Graduate (2017 & 2018)</em><br> <br> | ||
<em>Outstanding Graduate of Liaoning Province (2016)</em> | ||
<br> | ||
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<td style="padding:20px;width:100%;vertical-align:middle"> | ||
<heading>Academic Service (Reviewer)</heading> | ||
<br><br> | ||
<em> Journal Reviewer: TPAMI, TIP, SPM, TCYB, TCSVT, PR, TMLR, ... | ||
</em> | ||
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<em>Conference Reviewer: CVPR, ICCV, ECCV, ICLR, NeurIPS, ICML, AAAI, IJCAI, ...</em> | ||
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<heading>Invited Talk</heading> | ||
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<a href="https://jonbarron.info/">template from here</a> | ||
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</html> |
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