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<title>Guangchi Fang's Homepage</title>
<link rel="icon" type="image/jpg" href="./imgs/polyu_icon.png">
<link rel="stylesheet" href="./static/css/dics.original.css">
<script src="./static/js/event_handler.js"></script>
<script src="./static/js/dics.original.js"></script>
</head>
<body>
<table width="800" border="0" align="center" cellspacing="0" cellpadding="0">
<tbody>
<tr>
<td>
<!--SECTION 1 -->
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td width="68%" valign="middle">
<p align="center">
<name>Guangchi Fang 方广驰</name>
</p>
<p align="justify">
<!-- Hey, I'm Guangchi, a passionate explorer of 3D vision research. -->
<!-- Currently, I'm a first-year Ph.D. student at The Hong Kong Polytechnic University. I earned my master's and bachelor's degrees from Sun Yat-sen University and the University of Electronic Science and Technology of China, respectively. -->
Interested in 3D vision, particularly for 3D data processing inlcuding point cloud and neural representation.
<!-- I am interested in 3D vision and deep learning. Currently, I focus on 3D data processing, -->
<!-- typically for point cloud and neural representation. -->
<!-- </br></br>-->
<!-- In this summer (July - Oct 2019), I was a research intern at the Augumented Reality team of <a href="http://www.a9.com/">Amazon</a> (Palo Alto, CA).-->
<!-- In my M.Phil study, I interned at <a href="https://www.astri.org/">Hong Kong Applied Science and Technology Research Institute</a>.-->
<!-- In my undergraduate study, I was an exchange student at <a href="http://www.upv.es/">Universitat Politècnica de València</a> (Valencia, Spain).-->
</br>
</p>
<p align="center">
<a href="mailto:[email protected]">Email</a> /
<a href="https://github.com/fatPeter"> Github </a> /
<a href="https://scholar.google.com/citations?user=Jc1P0bcAAAAJ&hl=zh-CN">Google Scholar</a>
<!-- <a href="https://www.youtube.com/channel/UCaN36zlgHCvamlefa9mX8vg"> YouTube </a> -->
<!--
<a href="https://twitter.com/guangchi_fang"> Twitter </a> /
<a href="https://www.youtube.com/channel/UCaN36zlgHCvamlefa9mX8vg"> YouTube </a>
-->
<!--
<a href="https://www.zhihu.com/people/hu-qing-yong"> Blog </a> /
<a href="https://www.linkedin.com/in/qingyong-hu-b18061171/"> LinkedIn </a> /
<a href="https://twitter.com/home"> Twitter </a> /
<a href="https://scholar.google.com/citations?user=yboFNHEAAAAJ&hl=en">Google Scholar</a>
-->
</p>
</td>
<td align="right">
<a href="assets/mobilenerf/view_forwardfacing.html?obj=selfie">
<img src="./imgs/selfie1.png"
onmouseover="this.src='./imgs/selfie2.png'"
onmouseout="this.src='./imgs/selfie1.png'"
style="width: 135;"/>
</a>
</td>
<!-- <td align="right"><img class="hp-photo" src="./imgs/selfie.png" style="width: 240;"></td> -->
</tr>
</tbody>
</table>
<!--SECTION 2 -->
<!-- <table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td>
<heading>Research</heading>
<p align="justify">
I am interested in 3D vision and deep learning. Currently, I focus on 3D data processing,
typically for point cloud and neural representation.
</p>
</td>
</tr>
</tbody>
</table> -->
<!--SECTION 3 -->
<!--
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td>
<heading>News</heading>
<p><strong>[2022.03.27]</strong> Our <a href="https://link.springer.com/article/10.1007/s11263-022-01632-6">3DPointCaps++</a> has been accepted to IJCV 2022!
<p><strong>[2022.03.02]</strong> Our <a href="https://arxiv.org/abs/2203.09931">3DAC</a> has been accepted to CVPR 2022!
</td>
</tr>
</tbody>
</table>
-->
<!--SECTION 4 -->
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td>
<heading>Recent Work</heading>
</td>
</tr>
</tbody>
</table>
<!--SECTION 5 -->
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td width="20%"><img src="./imgs/mini_splatting2/small_sparse2.png" alt="PontTuset" width="180"
style="border-style: none"></td>
<td width="80%" valign="top">
<!-- <p><a href="https://fatpeter.github.io/">
<papertitle>Mini-Splatting2: Building 360 Scenes within Minutes via Aggressive Gaussian Densification
</papertitle>
</a>
<br><strong>G. Fang</strong> and B. Wang<br>
<a href="https://arxiv.org/pdf/2403.14166.pdf">ArXiv</a> /
<a href="https://github.com/fatPeter/mini-splatting"><font >Code</font></a> -->
<p><a href="https://arxiv.org/pdf/2411.12788">
<papertitle>Mini-Splatting2: Building 360 Scenes within Minutes
</papertitle>
</a>
<br><strong>G. Fang</strong> and B. Wang<br>
<a href="https://arxiv.org/pdf/2411.12788">ArXiv</a> /
<a href="https://github.com/fatPeter/mini-splatting2"><font >Code</font></a>
<p align="justify" style="font-size:13px"> Dense point cloud reconstruction through Gaussian Splatting enables fast scene optimization within minutes.
</p>
<p></p>
</td>
</tr>
</table>
<br>
<section class="section">
<div class="container is-max-desktop">
<div class="columns is-centered ">
<div class="column is-full-width">
<div class="container">
<div class="b-dics" style="width: 700px; font-weight: 600; transform: translateX(7%)">
<img src="./imgs/mini_splatting2/mvs.png" alt="MVS">
<img src="./imgs/mini_splatting2/3k_s.png" alt="Mini-Splatting2 (3K iter) ">
<img src="./imgs/mini_splatting2/8k.png" alt="Mini-Splatting2 (8K iter)">
</div>
</div>
<p style="text-align: center; font-size: 13px;"> Direct visualization of MVS points and Gaussian centers in MeshLab.</p>
</div>
</div>
</div>
</section>
<br>
<section class="section">
<div class="container is-max-desktop">
<div class="columns is-centered ">
<div class="column is-full-width">
<div class="container">
<div class="b-dics" style="width: 800px; font-weight: 600; transform: translateX(0%)">
<img src="./imgs/mini_splatting2/training_yellow.jpg">
</div>
</div>
<p style="text-align: center; font-size: 13px;">Training progress of 'bicycle' with a single RTX 3090 (3 minutes is sufficient for data loading, training and saving).</p>
</div>
</div>
</div>
</section>
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td width="20%"><img src="./imgs/mini_splatting/ms.jpg" alt="PontTuset" width="180"
style="border-style: none"></td>
<td width="80%" valign="top">
<p><a href="https://arxiv.org/pdf/2403.14166.pdf">
<papertitle>Mini-Splatting: Representing Scenes with a Constrained Number of Gaussians
</papertitle>
</a>
<br><strong>G. Fang</strong> and B. Wang<br>
<em>ECCV 2024 </em><br>
<a href="https://arxiv.org/pdf/2403.14166.pdf">ArXiv</a> /
<a href="https://github.com/fatPeter/mini-splatting"><font >Code</font></a>
<p align="justify" style="font-size:13px">Point cloud analysis in the context of Gaussian Splatting. Reorganizing the spatial distribution of Gaussians to construct an efficient scene representation.
</p>
<p></p>
</td>
</tr>
</table>
<!-- <br>
<section class="section">
<div class="container is-max-desktop">
<div class="columns is-centered ">
<div class="column is-full-width">
<div class="container">
<div class="b-dics" style="width: 460px; font-weight: 600; transform: translateX(36%)">
<img src="./imgs/mini_splatting/gs.jpg" alt="3DGS">
<img src="./imgs/mini_splatting/ms_d.jpg" alt="Mini-Splatting-D">
<img src="./imgs/mini_splatting/ms.jpg" alt="Mini-Splatting">
</div>
</div>
<p style="text-align: center; font-size: 13px;">Check out the teaser for details of spatial distribution.</p>
</div>
</div>
</div>
</section>
<br>
<section class="section">
<div class="container is-max-desktop">
<div class="columns is-centered ">
<div class="column is-full-width">
<div class="container">
<div class="b-dics" style="width: 800px; font-weight: 600; transform: translateX(0%)">
<img src="./imgs/mini_splatting/quant.png">
</div>
</div>
<p style="text-align: center; font-size: 13px;">Quantitative evaluation. All experimental settings are consistent with the original 3DGS implementation.</p>
</div>
</div>
</div>
</section> -->
<br>
<details>
<summary>
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<!-- <tr>
<td> -->
<heading>Publications</heading>
<!-- </td>
</tr> -->
</tbody>
</table>
</summary>
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td width="20%"><img src="./imgs/ACRF/teaser.jpg" alt="PontTuset" width="180"
style="border-style: none"></td>
<td width="80%" valign="top">
<p><a href="https://openreview.net/pdf?id=POFrdKvpea">
<papertitle>ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression
</papertitle>
</a>
<br><strong>G. Fang</strong>, Q. Hu, L. Wang, Y. Guo<br>
<em>ICLR 2024 </em><br>
<a href="https://openreview.net/pdf?id=POFrdKvpea">Paper</a> /
<a href="https://github.com/fatPeter/ACRF"><font >Code</font></a>
<p align="justify" style="font-size:13px">Compression of neural radiance fields via point cloud processing and 3D compression techniques.</p>
<p></p>
</td>
</tr>
</table>
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td width="20%"><img src="./imgs/3DAC/3DAC.png" alt="PontTuset" width="180"
style="border-style: none"></td>
<td width="80%" valign="top">
<p><a href="https://arxiv.org/abs/2203.09931">
<papertitle>3DAC: Learning Attribute Compression for Point Clouds
</papertitle>
</a>
<br><strong>G. Fang</strong>, Q. Hu, H. Wang, Y. Xu, Y. Guo<br>
<em>CVPR 2022 </em><br>
<a href="https://arxiv.org/abs/2203.09931">Paper</a> /
<a href="https://github.com/fatPeter/ThreeDAC"><font >Code</font></a> /
<!-- <a href="https://www.youtube.com/watch?v=QTkkI0AyvLM&t=205s">Presentation</a> / -->
<a href="imgs/3DAC/3DAC_cvpr_poster.pdf">Poster</a>
<p align="justify" style="font-size:13px">Point cloud attribute compression leveraging deep entropy coding.</p>
<p></p>
</td>
</tr>
</table>
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td width="20%"><img src="./imgs/3DPointCaps.png" alt="PontTuset" width="180"
style="border-style: none"></td>
<td width="80%" valign="top">
<p><a href="https://link.springer.com/article/10.1007/s11263-022-01632-6">
<papertitle>3DPointCaps++: Learning 3D Representations with Capsule Networks
</papertitle>
</a>
<br>Y. Zhao*, <strong>G. Fang*</strong>, Y. Guo, L. Guibas, F. Tombari, T. Birdal<br>
<em>IJCV 2022 </em> (* indicates equal contribution) <br>
<a href="https://link.springer.com/article/10.1007/s11263-022-01632-6">Paper</a> /
<a href="https://github.com/yongheng1991/3D-point-capsule-networks/tree/plus"><font >Code</font></a>
<!-- <a href="https://www.youtube.com/watch?v=04_Be2v6vYI"><font >Demo</font></a> -->
<p align="justify" style="font-size:13px">
Rigid and non-rigid point cloud representation learning based on capsule.
<p></p>
</td>
</tr>
</table>
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td width="20%"><img src="./imgs/SQN_2.gif" alt="PontTuset" width="180"
style="border-style: none"></td>
<td width="80%" valign="top">
<p><a href="https://arxiv.org/abs/2104.04891">
<papertitle>SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds
</papertitle>
</a>
<br>Q. Hu, B. Yang, <strong>G. Fang</strong>, A. Leonardis, Y. Guo, N. Trigoni, A.
Markham<br>
<em> ECCV 2022</em>
<br>
<!--<font color="red"><strong>..</strong></font><br>-->
<a href="https://arxiv.org/abs/2104.04891">ArXiv</a> /
<a href="https://github.com/QingyongHu/SQN"><font >Code</font></a>
<!-- <a href="https://www.youtube.com/watch?v=Q6wICSRRw3s&t=4s">Demo</a> /
<a href="https://www.youtube.com/watch?v=N0UAeY31msY&t=4s">Annotation</a> -->
<!--<iframe src="https://ghbtns.com/github-btn.html?user=QingyongHu&repo=SQN&type=star&count=true&size=small"
frameborder="0" scrolling="0" width="120px" height="20px"></iframe>-->
<p align="justify" style="font-size:13px">
Weakly supervised point cloud segmentation through point query.</p>
<p></p>
</td>
</tr>
</table>
</details>
<!--SECTION 4 -->
<!-- <table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td>
<heading>Publications</heading>
</td>
</tr>
</tbody>
</table> -->
<!--SECTION 6 -->
<!--
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td>
<heading>Individual Project</heading>
</td>
</tr>
</tbody>
</table>
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
<tr>
<td width="20%"><img src="./imgs/project/urban_rec/demo.gif" alt="PontTuset" width="180"
style="border-style: none"></td>
<td width="80%" valign="top">
<p>
<papertitle>Lidar-based Urban Scene Reconstruction</papertitle><br>
<a href="https://www.youtube.com/watch?v=-wwTcr_4UVE&t=4s">Presentation</a><br>
<p align="justify" style="font-size:13px">Lidar-based Urban Scene Reconstruction. A simple pipeline includes plane segmentation and multi-frame point clouds registration.</p>
<p></p>
</td>
</tr>
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<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tbody>
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<td width="20%"><img src="./imgs/project/seed_filling/demo.gif" alt="PontTuset" width="180"
style="border-style: none"></td>
<td width="80%" valign="top">
<p>
<papertitle>Tracking with Seed Filling
</papertitle>
</a><br>
<a href="https://github.com/fatPeter/Misc/tree/main/projects/Tracking_with_Seed_Filling"><font >Code</font></a> /
<a href="https://www.youtube.com/watch?v=rGaUNnhVKno">Demo</a>
<p align="justify" style="font-size:13px">Tracking with seed filling on a laptop. The center and the orientation of 2D objects are marked.</p>
<p></p>
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<td>
<heading>Teaching</heading>
<p><strong>Fall, 2020</strong>:   
C programming
</a> (Sun Yat-sen University). </p>
</td>
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</table>
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<heading>Reviewer Services</heading>
<ul style="list-style-type:disc;">
<li>
<a href="https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=34">
IEEE Transactions on Pattern Analysis and Machine
Intelligence (IEEE TPAMI)
<li>
<a href="https://www.springer.com/journal/11263">
International Journal of Computer Vision (IJCV)
<li>
<a href="https://iclr.cc/">
International Conference on Learning Representations
(ICLR)
<li>
<a href="https://icml.cc/">
International Conference on Machine Learning
(ICML)
<li>
<a href="https://nips.cc/">
Conference on Neural Information Processing Systems
(NeurIPS)
<li>
<a href="http://cvpr2021.thecvf.com/">
IEEE Conference on Computer Vision and Pattern
Recognition (CVPR)
<li>
<a href="http://iccv2021.thecvf.com/home">
International Conference on Computer Vision (ICCV)
<li>
<a href="http://iccv2021.thecvf.com/home">
European Conference on Computer Vision (ECCV)
<li>
<a href="http://www.icra2021.org/">
International Conference on Robotics and
Automation (ICRA)
<li>
<a href="http://www.ieee-ras.org/conferences-workshops/financially-co-sponsored/iros">
IEEE/RSJ International Conference on Intelligent
Robots
and Systems (IROS)
<li><a href="https://bmvc2020.github.io/"> British
Machine Vision Conference (BMVC)
<li>
<a href="https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=83">
IEEE Transactions on Image Processing (IEEE TIP)
<li>
<a href="https://www.sciencedirect.com/journal/information-fusion">
IEEE Transactions on Circuits and Systems for Video
Technology (IEEE TCSVT)
<li>
<a href="https://www.journals.elsevier.com/computers-and-graphics">
Computers & Graphics (C&G)
<li>
<a href="https://www.sciencedirect.com/journal/information-fusion">
Information Fusion
</ul>
</td>
</tr>
</table>
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<td><br>
<!--<p align="right"><font size="3">Erdös = ? </font><br> -->
<p align="right"><font size="2"> <a
href="http://www.cs.berkeley.edu/~barron/">Thanks.</a></font>
</p>
</td>
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