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<!DOCTYPE html>
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<title>Motion Mamba</title>
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<h1 class="title is-1 publication-title">Motion Mamba: Efficient and Long Sequence Motion Generation</h1>
<div class="is-size-5 publication-authors">
<!-- Paper authors -->
<span class="author-block">
<a href="https://steve-zeyu-zhang.github.io/" target="_blank">Zeyu Zhang</a><sup>1</sup><sup>2</sup><sup>*</sup><sup>†</sup>,</span>
<span class="author-block">
<a href="https://www.linkedin.com/in/akideliu/" target="_blank">Akide Liu</a><sup>1</sup><sup>*</sup>,</span>
<span class="author-block">
<a href="https://mbzuai.ac.ae/study/faculty/ian-reid/" target="_blank">Ian Reid</a><sup>3</sup>,</span>
<span class="author-block">
<a href="http://users.cecs.anu.edu.au/~hartley/" target="_blank">Richard Hartley</a><sup>2</sup>,</span>
<span class="author-block">
<a href="https://bohanzhuang.github.io/" target="_blank">Bohan Zhuang</a><sup>1</sup>,</span>
<span class="author-block">
<a href="https://ha0tang.github.io/" target="_blank">Hao Tang</a><sup>4</sup><sup>✉</sup>
</span>
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<span class="author-block"><font size="4"><sup>1</sup> <a href="https://www.monash.edu/" target="_blank">Monash University</a></font></span>
<span class="author-block"><font size="4"><sup>2</sup> <a href="https://www.anu.edu.au/" target="_blank">The Australian National University</a></font></span><br>
<span class="author-block"><font size="4"><sup>3</sup> <a href="https://mbzuai.ac.ae/" target="_blank">Mohamed bin Zayed University of Artificial Intelligence</a></font></span>
<span class="author-block"><font size="4"><sup>4</sup> <a href="https://english.pku.edu.cn/" target="_blank">Peking University</a></font></span><br>
<p style="height: 10px;"> </p>
<span class="author-block"><font size="5"><a href="https://eccv2024.ecva.net/" target="_blank"><b style="color: OrangeRed;">ECCV 2024</b></a></font></span><br>
<span class="eql-cntrb"><small><sup>*</sup>Equal Contribution.</small></span>
<span class="eql-cntrb"><small><sup>✉</sup>Corresponding author.</small></span><br>
<span class="eql-cntrb"><small><sup>†</sup>Work done while being a research assistant at Monash University.</small></span>
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<span>arXiv</span>
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</section>
<div class="news">
<h2><font size="4"> <b>News:</b> </font></h2>
<ul>
<li><b>(07/22/2024)</b> 🎉 Our paper was invited for a talk at <a href="https://www.mihoyo.com/"><b>miHoYo</b></a>. You can find our slides <a href="https://steve-zeyu-zhang.github.io/MotionMamba/static/pdfs/Motion_Mamba_Slides_miHoYo.pdf"><b>here</b></a>!</li>
</ul>
<ul>
<li><b>(07/05/2024)</b> 🎉 Our paper has been highlighted twice by <a href="https://wx.zsxq.com/dweb2/index/topic_detail/5122458815888184"><b>CVer</b></a>!</li>
</ul>
<ul>
<li><b>(07/02/2024)</b> 🎉 Our paper has been accepted to <a href="https://eccv2024.ecva.net/"><b style="color: OrangeRed;">ECCV 2024</b></a>!</li>
</ul>
<ul>
<li><b>(03/15/2024)</b> 🎉 Our paper has been highlighted by <a href="https://twitter.com/Marktechpost/status/1768770427680424176"><b>MarkTechPost</b></a>!</li>
</ul>
<ul>
<li><b>(03/13/2024)</b> 🎉 Our paper has been featured in <a href="https://twitter.com/_akhaliq/status/1767750847239262532"><b>Daily Papers</b></a>!</li>
</ul>
<ul>
<li><b>(03/13/2024)</b> 🎉 Our paper has been highlighted by <a href="https://wx.zsxq.com/dweb2/index/topic_detail/1522541851241522"><b>CVer</b></a>!</li>
</ul>
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Aliquam vitae elit ullamcorper tellus egestas pellentesque. Ut lacus tellus, maximus vel lectus at, placerat pretium mi. Maecenas dignissim tincidunt vestibulum. Sed consequat hendrerit nisl ut maximus.
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<h2 class="title is-3">Abstract</h2>
<div class="content has-text-justified">
<p>
Human motion generation stands as a significant pursuit in generative computer vision,
while achieving long-sequence and efficient motion generation remains challenging.
Recent advancements in state space models (SSMs), notably Mamba,
have showcased considerable promise in long sequence modeling with an efficient
hardware-aware design, which appears to be a promising direction to build motion
generation model upon it. Nevertheless, adapting SSMs to motion generation
faces hurdles since the lack of a specialized design architecture to model motion sequence.
To address these challenges, we propose <b>Motion Mamba</b>,
a simple and efficient approach that presents the pioneering motion
generation model utilized SSMs. Specifically, we design a <b>Hierarchical Temporal Mamba</b>
(<b>HTM</b>) block to process temporal data by ensemble varying numbers of isolated
SSM modules across a symmetric U-Net architecture aimed at preserving motion
consistency between frames. We also design a <b>Bidirectional Spatial Mamba</b> (<b>BSM</b>)
block to bidirectionally process latent poses, to enhance accurate motion generation
within a temporal frame. Our proposed method achieves up to <b>50%</b> FID improvement and up to
<b>4</b> times faster on the HumanML3D and KIT-ML datasets compared to the previous best
diffusion-based method, which demonstrates strong capabilities of high-quality long
sequence motion modeling and real-time human motion generation.
</p>
</div>
</div>
</div>
</div>
</section>
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<h2 class="title is-3">Visualization</h2>
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<p style="height: 10px;"> </p><br>
<p>The character performs a <b>backflip</b> when doing <b>exercise</b>.</p><br>
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<p>The character first <b>walks</b>, then <b>jumps</b>, and later <b>runs</b> in a <b>straight line</b>.</p><br>
<p style="height: 5px;"> </p>
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<source src="static/videos/circle.mp4"
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<p>The character walks in <b>two</b> consecutive <b>clockwise</b> circles.</p><br>
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<source src="static/videos/badminton.mp4"
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<p style="height: 10px;"> </p><br>
<p>The character executes a <b>smash</b> during a <b>badminton</b> match.</p><br>
<p style="height: 5px;"> </p>
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<p>The character performs a <b>street dance</b>.</p><br>
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<p style="height: 10px;"> </p><br>
<p>The character <b>sits</b> on the ground, then <b>stands up</b>, <b>picks up</b> a newspaper from the ground, and starts to <b>read</b>.</p><br>
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<p style="height: 10px;"> </p><br>
<p>We compared the proposed <b>Motion Mamba</b> with well-established state-of-the-art methods such as <a href="https://mingyuan-zhang.github.io/projects/MotionDiffuse.html">MotionDiffuse</a>, <a href="https://guytevet.github.io/mdm-page/">MDM</a>, and <a href="https://chenxin.tech/mld/">MLD</a>. We presented three distinct motion prompts and visualized them in the form of motion sequence. The results demonstrated our superior performance compared to existing methods.</p><br>
</div>
<p style="height: 50px;"> </p>
<img src="static/images/more_demo.svg" style="width: 50%;">
<div class="image-description">
<p style="height: 10px;"> </p><br>
<p>We have included extra examples to showcase the proposed <b>Motion Mamba</b> model. These examples feature randomly selected prompts sourced from <a href="https://github.com/EricGuo5513/HumanML3D">HumanML3D</a>, providing additional visualizations of the model's capabilities.</p><br>
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</section>
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<section class="section hero is-light">
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<h2 class="title is-3">Methodology</h2>
</div>
<p style="height: 50px;"> </p>
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<center>
<img src="static/images/block.svg" style="width: 50%;">
<div class="image-description">
<p style="height: 10px;"> </p><br>
<p>This figure illustrates the architecture of the proposed <b>Motion Mamba</b> model. Each of encoder and decoder blocks consists of a <b>Hierarchical Temporal Mamba block (HTM)</b> and a <b>Bidirectional Spatial Mamba (BSM)</b> block, which possess hierarchical scan and bidirectional scan within SSM layers respectively. This symmetric distribution of scans ensure a balanced and coherence framework across the encoder-decoder architecture.</p><br>
</div>
</center>
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</section>
<section class="section hero is-small">
<div class="my-hero-body">
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<h2 class="title is-3">Performance</h2>
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<p><b>Motion Mamba</b> has achieved significantly superior performance on long squence modeling and motion generation efficiency compared with other well-designed state-of-the-art methods such as <a href="https://chenxin.tech/mld/">MLD [6]</a>, <a href="https://mingyuan-zhang.github.io/projects/MotionDiffuse.html">MotionDiffuse [53]</a>, and <a href="https://guytevet.github.io/mdm-page/">MDM [49]</a></p><br>
</div>
</center>
</div>
</div>
</section>
<!-- Paper poster -->
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<div class="hero-body">
<div class="container">
<h2 class="title">Poster</h2>
<iframe src="static/pdfs/Motion_Mamba_Poster.pdf" width="100%" height="1000">
</iframe>
</div>
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</section>
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<!--BibTex citation -->
<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h2 class="title">BibTeX</h2>
<pre><code>@article{zhang2024motion,
title={Motion Mamba: Efficient and Long Sequence Motion Generation with Hierarchical and Bidirectional Selective SSM},
author={Zhang, Zeyu and Liu, Akide and Reid, Ian and Hartley, Richard and Zhuang, Bohan and Tang, Hao},
journal={arXiv preprint arXiv:2403.07487},
year={2024}
}</code></pre>
</div>
</section>
<!--End BibTex citation -->
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