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research.html
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.1//EN"
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<html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en">
<head>
<meta name="generator" content="jemdoc, see http://jemdoc.jaboc.net/" />
<meta http-equiv="Content-Type" content="text/html;charset=utf-8" />
<link rel="stylesheet" href="jemdoc.css" type="text/css" />
<title>Research</title>
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<table summary="Table for page layout." id="tlayout">
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<td id="layout-menu">
<div class="menu-category">Likun Cai</div>
<div class="menu-item"><a href="index.html">About me</a></div>
<div class="menu-item"><a href="research.html" class="current">Research</a></div>
<div class="menu-item"><a href="teaching.html">Teaching</a></div>
<div class="menu-item"><a href="cv/likuncai_cv.pdf">CV</a></div>
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<td id="layout-content">
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<h1>Research</h1>
</div>
<p><a href="https://scholar.google.com/citations?user=5r6IM_gAAAAJ&hl=zh-CN" target=“blank”>Google Scholar</a>
</p>
<h2>2024</h2>
<ul>
<li><p>OpenAnnotate3D: Open-Vocabulary Auto-Labeling System for Multi-modal 3D Data <br />
Yijie Zhou, <b>Likun Cai</b>, Xianhui Cheng, Zhongxue Gan, Xiangyang Xue, Wenchao Ding <br />
<i>International Conference on Robotics and Automation. 2024</i> <br />
[<a href="https://arxiv.org/pdf/2310.13398.pdf" target=“blank”>Paper</a>]
</p>
</li>
</ul>
<h2>2022</h2>
<ul>
<li><p>BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training <br />
<b>Likun Cai</b>, Zhi Zhang, Yi Zhu, Li Zhang, Mu Li, Xiangyang Xue <br />
<i>Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops. 2022: 4777-4787</i> <br />
[<a href="https://arxiv.org/abs/2203.13249" target=“blank”>Paper</a>] [<a href="https://github.com/amazon-science/bigdetection" target=“blank”>Code</a>]
</p>
</li>
</ul>
<h2>2020</h2>
<ul>
<li><p>Utilizing Amari-Alpha Divergence to Stabilize the Training of Generative Adversarial Networks <br />
<b>Likun Cai</b>, Yanjie Chen, Ning Cai, Wei Cheng, Hao Wang <br />
<i>Entropy 2020, 22(4), 410</i> <br />
[<a href="https://www.mdpi.com/1099-4300/22/4/410" target=“blank”>Paper</a>] [<a href="https://github.com/cailk/AlphaGAN" target=“blank”>Code</a>]
</p>
</li>
</ul>
<ul>
<li><p>Super-Resolution Coding Defense Against Adversarial Examples <br />
Yanjie Chen, <b>Likun Cai</b>, Wei Cheng, Hao Wang <br />
<i>Proceedings of the 2020 International Conference on Multimedia Retrieval. 2020: 189-197</i> <br />
[<a href="https://dl.acm.org/doi/abs/10.1145/3372278.3390689" target=“blank”>Paper</a>]
</p>
</li>
</ul>
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