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index.html
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<script src="http://www.google.com/jsapi" type="text/javascript"></script>
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<html>
<head>
<title>HMDiff</title>
<meta property="og:image" content="Path to my teaser.png"/> <!-- Facebook automatically scrapes this. Go to https://developers.facebook.com/tools/debug/ if you update and want to force Facebook to rescrape. -->
<meta property="og:title" content="Creative and Descriptive Paper Title." />
<meta property="og:description" content="Paper description." />
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gtag('js', new Date());
gtag('config', 'UA-75863369-6');
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<span style="font-size:36px">Distribution-Aligned Diffusion for Human Mesh Recovery</span>
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<span style="font-size:22px"><sup>1</sup><a href="https://scholar.google.com/citations?user=BDEOhasAAAAJ&hl=zh-CN&oi=ao">Lin Geng Foo</a>,</span>
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<span style="font-size:22px"><sup>1</sup><a href="https://scholar.google.com/citations?user=ZV-ThegAAAAJ&hl=zh-CN">JIA GONG</a>,</span>
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<span style="font-size:22px"><sup>2</sup><a href="https://scholar.google.com/citations?user=zFyT_gwAAAAJ&hl=zh-CN">Hossein Rahmani</a>,</span>
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<span style="font-size:22px"><sup>1</sup><a href="https://people.sutd.edu.sg/~jun_liu/">Jun Liu</a><sup>#</sup>,</span>
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<span style="font-size:24px"><sup>1</sup>Singapore University of Technology and Design</span>
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<span style="font-size:24px"><sup>2</sup>Lancaster University</span>
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<span style="font-size:24px"><sup>#</sup>corresponding author</span>
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<span style="font-size:24px"><a href='https://openaccess.thecvf.com/content/ICCV2023/html/Foo_Distribution-Aligned_Diffusion_for_Human_Mesh_Recovery_ICCV_2023_paper.html'>[Paper]</a></span>
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This was a template originally made for <a href="http://richzhang.github.io/colorization/">Colorful Image Colorization</a>. The code can be found in this <a href="https://github.com/richzhang/webpage-template">repository</a>.
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<center><h1>Abstract</h1></center>
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<td>
Recovering a 3D human mesh from a single RGB image is a challenging task due to depth ambiguity and self-occlusion, resulting in a high degree of uncertainty.
Meanwhile, diffusion models have recently seen much success in generating high-quality outputs by progressively denoising noisy inputs.
Inspired by their capability, we explore a diffusion-based approach for human mesh recovery, and propose a Human Mesh Diffusion (HMDiff) framework which frames mesh recovery as a reverse diffusion process.
We also propose a Distribution Alignment Technique (DAT) that injects input-specific distribution information into the diffusion process, and provides useful prior knowledge to simplify the mesh recovery task.
Our method achieves state-of-the-art performance on three widely used datasets.
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<center><h1>Talk</h1></center>
<p align="center">
<iframe width="660" height="395" src="https://www.youtube.com/embed/dQw4w9WgXcQ" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen align="center"></iframe>
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<span style="font-size:28px"><a href=''>[Slides]</a>
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<center><h1>Our method</h1></center>
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<td><img class="round" style="width:850px" src="./Pipeline_figure.png"/></td>
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Illustration of the proposed Human Mesh Diffusion (HMDiff) framework with the Distribution Alignment Technique (DAT).
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<center><h1>Our Visualization</h1></center>
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<source src="./HMDiff_GIF.mp4" type=video/mp4>
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<span style="font-size:28px"> <a href=''>[Code]</a>
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<center><h1>Paper</h1></center>
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<td><a href="https://openaccess.thecvf.com/content/ICCV2023/html/Foo_Distribution-Aligned_Diffusion_for_Human_Mesh_Recovery_ICCV_2023_paper.html"><img class="layered-paper-big" style="height:175px" src="./paper.png"/></a></td>
<td><span style="font-size:14pt">Foo, L. G., Gong, J., Rahmani, H., & Liu, J.<br>
<b>>Distribution-Aligned Diffusion for Human Mesh Recovery.</b><br>
In ICCV, 2023.<br>
(hosted on <a href="https://openaccess.thecvf.com/content/ICCV2023/html/Foo_Distribution-Aligned_Diffusion_for_Human_Mesh_Recovery_ICCV_2023_paper.html">ICCV</a>)<br>
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<td><span style="font-size:14pt"><center>
<a href="./bibtex.txt">[Bibtex]</a>
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<center><h1>Acknowledgements</h1></center>
This template was originally made by <a href="http://web.mit.edu/phillipi/">Phillip Isola</a> and <a href="http://richzhang.github.io/">Richard Zhang</a> for a <a href="http://richzhang.github.io/colorization/">colorful</a> ECCV project; the code can be found <a href="https://github.com/richzhang/webpage-template">here</a>.
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