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<script type="module" src="https://unpkg.com/@google/model-viewer/dist/model-viewer.min.js"></script>
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<html xmlns="http://www.w3.org/1999/xhtml"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<link rel="StyleSheet" href="./files/style.css" type="text/css" media="all">
<title>OmniMotionGPT</title>
<style type="text/css">
body {
font-family : Times;
background-color : #f2f2f2;
font-size : 15px;
}
.content {
width : 800px;
padding : 25px 25px;
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background-color : #fff;
border-radius: 20px;
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.description {
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white-space: pre;
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a, a:visited {
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#authors {
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#conference {
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h1 {
text-align : center;
font-family : Times;
font-size : 35px;
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h2 {
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p {
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big {
font-family : Times;
font-size : 20px;
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li {
margin : 10px 0;
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.samples {
float : left;
width : 50%;
text-align : center;
}
.cond {
float : left;
margin : 0 40px;
}
.cond-container {
width : 700px;
margin : 0 auto;
text-align : center;
}
#vidalign {
display: block;
margin: 0px;
padding: 0px;
position: relative;
top: 90px;
height: auto;
max-width: auto;
overflow-y: hidden;
overflow-x:auto;
word-wrap:normal;
white-space:nowrap;
}
.footnote-marker {
display: inline-block; /* Use block if you want the asterisk on a separate line */
text-align: center;
font-size: smaller;
width: 100%; /* Full width if you want it on a separate line */
}
.footnote-container {
text-align: center; /* Centers text within the container */
/* Other styling as needed */
}
.footnotes {
text-align: center;
font-size: smaller;
color: grey;
}
.video-container {
display: flex;
flex-wrap: wrap;
justify-content: center;
margin-top: 30px;
align-items: center; /* This centers the children vertically if they are of different heights */
}
.video-wrapper {
flex: 1;
margin-right: 2px;
margin-left: 2px;
max-width: calc(20% - 4px);
/* 33.33% for 3 videos per row, subtracting margins */
height: auto;
text-align: center;
}
.video {
max-width: 100%; /* Make sure the video fills the wrapper */
height: auto;
display: block; /* This can help with centering in some cases */
margin: 0 auto; /* This centers the video if it's not already */
}
.caption {
text-align: center; /* other styling as needed */
}
.container {
display: flex;
justify-content: center; /* Center horizontally */
align-items: center; /* Center vertically */
}
figure {
text-align: center; /* Centers the caption text */
width: 200px; /* Matches the width of the model-viewer */
margin: auto; /* Centers the figure in the space allotted to it */
}
figcaption {
margin-top: 8px; /* Spacing between the model-viewer and the caption */
width: 100%; /* Ensures the caption is as wide as its parent figure */
}
</style>
</head>
<body>
<div class="content content-title" style="text-align: center;">
<h1>OmniMotionGPT: Animal Motion Generation with Limited Data</h1>
<p id="authors">
<table align="center" style="width:100%; text-align:center; table-layout: fixed">
<tr>
<th><a href="https://zhangsihao-yang.github.io/">Zhangsihao Yang<sup>1*</sup></a></th>
<th><a href="https://sites.google.com/view/mingyuan-zhou/home">Mingyuan Zhou<sup>2</sup></a></th>
<th><a href="https://shanmy.github.io/">Mengyi Shan<sup>3</sup></a></th>
<th><a href="https://bbwen.github.io/">Bingbing Wen<sup>3</sup></a></th>
<th><a href="">Ziwei Xuan<sup>2</sup></a></th>
</tr>
</table>
<table align="center" style="width:100%; text-align:center; table-layout: fixed">
<tr>
<th><a href="https://scholar.google.com/citations?user=ycEHnWoAAAAJ&hl=en">Mitch Hill<sup>2</sup></a></th>
<th><a href="https://scholar.google.com/citations?user=tG-WDLwAAAAJ&hl=en">Junjie Bai<sup>2</sup></a></th>
<th><a href="http://maple-lab.net/gqi/">Guo-Jun Qi<sup>24</sup></a></th>
<th><a href="https://gsl.lab.asu.edu/yalin-wang/">Yalin Wang<sup>1</sup></a></th>
</tr>
</table>
<table align="center" style="width:100%; text-align:center; table-layout: fixed">
<th><sup>1</sup>Arizona State University, USA</th>
<th><sup>2</sup>OPPO Seattle Research Center, USA</th>
<th><sup>3</sup>University of Washington, USA</th>
<th><sup>4</sup>Westlake University, China</th>
</table>
</p>
<!-- Footnotes Section -->
<!-- <div class="footnote-container">
<span class="footnote-marker"></span> * Work done while interning at OPPO.
</div> -->
</div>
<div class="content">
<h2> Generated Motions from Text Descriptions</h2>
<div class="container">
<!-- First model viewer -->
<figure>
<model-viewer
style="width: 200px; height: 200px;"
id="meshViewer1"
autoplay
ar
shadow-intensity="1"
shadow-softness="1"
ar-modes="webxr scene-viewer quick-look"
environment-image="neutral"
camera-controls
camera-target="0 0 0">
</model-viewer>
<figcaption><em>"A dog jumps forward and swings its arms."</em></figcaption>
</figure>
<!-- Second model viewer -->
<figure>
<model-viewer
style="width: 200px; height: 200px;"
id="meshViewer2"
autoplay
ar
shadow-intensity="1"
shadow-softness="1"
ar-modes="webxr scene-viewer quick-look"
environment-image="neutral"
camera-controls
camera-target="0 0 0">
</model-viewer>
<figcaption><em>"A bear passes objects from the left to the right initially heavy but then lighter objects."</em></figcaption>
</figure>
<!-- Third model viewer -->
<figure>
<model-viewer
style="width: 200px; height: 200px;"
id="meshViewer3"
autoplay
ar
shadow-intensity="1"
shadow-softness="1"
ar-modes="webxr scene-viewer quick-look"
environment-image="neutral"
camera-controls
camera-target="0 0 0">
</model-viewer>
<figcaption><em>"A moose jogs on the spot."</em></figcaption>
</figure>
<!-- Fourth model viewer -->
<figure>
<model-viewer
style="width: 200px; height: 200px;"
id="meshViewer4"
autoplay
ar
shadow-intensity="1"
shadow-softness="1"
ar-modes="webxr scene-viewer quick-look"
environment-image="neutral"
camera-controls
camera-target="0 0 0">
</model-viewer>
<figcaption><em>"A dog puts its hands on the floor and does a handstand."</em></figcaption>
</figure>
</div>
<!-- Script for the first model viewer -->
<script>
const meshes1 = [];
for (let i = 0; i <= 67; i++) {
let paddedNumber = String(i).padStart(3, '0');
meshes1.push(`meshes/000074/${paddedNumber}.glb`);
}
let currentIndex1 = 0;
const meshViewer1 = document.getElementById('meshViewer1');
function displayNextMesh1() {
meshViewer1.setAttribute('src', meshes1[currentIndex1]);
currentIndex1 = (currentIndex1 + 1) % meshes1.length;
}
setInterval(displayNextMesh1, 100); // You may want to increase this interval
displayNextMesh1();
</script>
<!-- Script for the second model viewer -->
<script>
const meshes2 = [];
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let paddedNumber = String(i).padStart(3, '0');
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function displayNextMesh2() {
meshViewer2.setAttribute('src', meshes2[currentIndex2]);
currentIndex2 = (currentIndex2 + 1) % meshes2.length;
}
setInterval(displayNextMesh2, 100); // You may want to increase this interval
displayNextMesh2();
</script>
<!-- Script for the third model viewer -->
<script>
const meshes3 = [];
for (let i = 0; i <= 71; i++) {
let paddedNumber = String(i).padStart(3, '0');
meshes3.push(`meshes/000099/${paddedNumber}.glb`);
}
let currentIndex3 = 0;
const meshViewer3 = document.getElementById('meshViewer3');
function displayNextMesh3() {
meshViewer3.setAttribute('src', meshes3[currentIndex1]);
currentIndex3 = (currentIndex3 + 1) % meshes3.length;
}
setInterval(displayNextMesh3, 100); // You may want to increase this interval
displayNextMesh3();
</script>
<!-- Script for the fourth model viewer -->
<script>
const meshes4 = [];
for (let i = 0; i <= 57; i++) {
let paddedNumber = String(i).padStart(3, '0');
meshes4.push(`meshes/000024/${paddedNumber}.glb`);
}
let currentIndex4 = 0;
const meshViewer4 = document.getElementById('meshViewer4');
function displayNextMesh4() {
meshViewer4.setAttribute('src', meshes4[currentIndex1]);
currentIndex4 = (currentIndex4 + 1) % meshes4.length;
}
setInterval(displayNextMesh4, 100); // You may want to increase this interval
displayNextMesh4();
</script>
<!-- Meta Information -->
<div style="margin: 12px; text-align: left; border-top: 1px solid lightgray; padding-top: 12px;">
<a href="">
<strong>[Data]</strong>
</a>
<a href="">
<strong>[Code]</strong>
</a>
<a href="https://arxiv.org/abs/2311.18303">
<strong>[Paper]</strong>
</a>
</div>
</div>
<div class="content">
<h2>Abstract</h2>
<p>
Our paper aims to generate diverse and realistic animal motion sequences from textual descriptions, without a large-scale animal text-motion dataset. While the task of text-driven human motion synthesis is already extensively studied and benchmarked, it remains challenging to transfer this success to other skeleton structures with limited data. In this work, we design a model architecture that imitates Generative Pretraining Transformer (GPT), utilizing prior knowledge learned from human data to the animal domain. We jointly train motion autoencoders for both animal and human motions and at the same time optimize through the similarity scores among human motion encoding, animal motion encoding, and text CLIP embedding. Presenting the first solution to this problem, we are able to generate animal motions with high diversity and fidelity, quantitatively and qualitatively outperforming the results of training human motion generation baselines on animal data. Additionally, we introduce AnimalML3D, the first text-animal motion dataset with 1240 animation sequences spanning 36 different animal identities. We hope this dataset would mediate the data scarcity problem in text-driven animal motion generation, providing a new playground for the research community.
</p>
<div>
<img src="./figures/website_teaser.png" width="95%">
</div>
</div>
<div class="content">
<h2>Visual Comparison</h2>
<!-- <div style="float: right; width:70px; margin-top: 0px; margin-bottom: 25px"></div> -->
<div style="width:70px; margin-top: 0px; margin-bottom: 25px"></div>
<div class="video-container" style="margin-top: 0px;">
<div class="video-wrapper">
<p class="caption">T2M-GPT</p>
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000049_t2mgpt.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<p class="caption">MotionGPT</p>
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000049_motiongpt.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<p class="caption">MDM</p>
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000049_md.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<p class="caption">MotionDiffuse</p>
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000049_mdm.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<p class="caption">OMGPT (Ours)</p>
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000049_omgpt.webm" type="video/mp4">
</video>
</div>
</div>
<p style="text-align: center;"><em>"A bear uplift his right hand and moving it fast again and again."</em></p>
<div class="video-container" style="margin-top: 0px;">
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000054_t2mgpt.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000054_motiongpt.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000054_md.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000054_mdm.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000054_omgpt.webm" type="video/mp4">
</video>
</div>
</div>
<p style="text-align: center;"><em>"A bear is waving with his right hand."</em></p>
<div class="video-container" style="margin-top: 0px;">
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000074_t2mgpt.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000074_motiongpt.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000074_md.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000074_mdm.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000074_omgpt.webm" type="video/mp4">
</video>
</div>
</div>
<p style="text-align: center;"><em>"A dog jumps forward and swings its arms."</em></p>
<div class="video-container" style="margin-top: 0px;">
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000087_t2mgpt.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000087_motiongpt.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000087_md.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000087_mdm.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/000087_omgpt.webm" type="video/mp4">
</video>
</div>
</div>
<p style="text-align: center;"><em>"A bear standing brings hands together in front of him to applaud."</em></p>
</div>
<div class="content">
<h2>Ablation Study</h2>
<div style="width:70px; margin-top: 0px; margin-bottom: 25px"></div>
<div class="video-container" style="margin-top: 0px;">
<div class="video-wrapper">
<p class="caption">A</p>
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/A.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<p class="caption">B</p>
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/B.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<p class="caption">C</p>
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/C.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<p class="caption">D</p>
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/D.webm" type="video/mp4">
</video>
</div>
<div class="video-wrapper">
<p class="caption">E</p>
<video class="video" onclick="setAttribute('controls', 'true');" autoplay loop muted>
<source src="videos/E.webm" type="video/mp4">
</video>
</div>
</div>
<p style="text-align: center;"><em>"A puma throws an object with their right hand and catch an object with both hands."</em></p>
<h2>More Our Results</h2>
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<p class="caption"><em>"A dog raises right hand, waves, ..."</em></p>
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<p class="caption"><em>"Moose stretches by wrapping one arm ..."</em></p>
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<p class="caption"><em>"Dog stomps his left feet."</em></p>
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<p class="caption"><em>"A dog walks backwards."</em></p>
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<p class="caption"><em>"A puma raises their left hand ..."</em></p>
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<h3>Framework Overview</h3>
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<img src="./figures/pipeline.png" width="95%">
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<p>
We train part (a) and part (b) at the same time.
In (a), we train two motion autoencoders simultaneously, each within their domain.
In (b), human motion is fed into the human motion encoder to produce a semantic-aware, subject-invariant latent code <em>Z</em>.
The CLIP feature of the subject-translated sentence and <em>Z</em> are concatenated together and passed into the animal decoders.
During inference in (c), we generate animal motions based on human motion sequences sampled from generative models.
Details on the architecture, loss functions, and inference process are elaborated in the paper.
</p>
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<h2>Bibtex</h2>
<p class="description">
@misc{yang2023omnimotiongpt,
title={OmniMotionGPT: Animal Motion Generation with Limited Data},
author={Zhangsihao Yang and Mingyuan Zhou and Mengyi Shan and Bingbing Wen and Ziwei Xuan and Mitch Hill
and Junjie Bai and Guo-Jun Qi and Yalin Wang},
year={2023},
eprint={2311.18303},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
</p>
</div>
<!-- <div class="content">
<h2>Related work</h2>
<p>
<a href="https://chhankyao.github.io/hi-lassie/">Hi-LASSIE: High-Fidelity Articulated Shape and Skeleton Discovery from Sparse Image Ensemble. CVPR 2023.</a><br>
<a href="https://bite.is.tue.mpg.de/">BITE: Beyond Priors for Improved Three-D Dog Pose Estimation. CVPR 2023.</a><br>
<a href="https://barc.is.tue.mpg.de/">BARC: Learning to Regress 3D Dog Shape from Images by Exploiting Breed Information. CVPR 2022.</a><br>
<a href="https://chhankyao.github.io/lassie/">LASSIE: Learning Articulated Shape from Sparse Image Ensemble via 3D Part Discovery. NeurIPS 2022.</a><br>
<a href="https://jasonyzhang.com/ners/">NeRS: Neural Reflectance Surfaces for Sparse-View 3D Reconstruction in the Wild. NeurIPS 2021.</a><br>
<a href="https://nileshkulkarni.github.io/acsm/">Articulation Aware Canonical Surface Mapping. CVPR 2020.</a><br>
<a href="https://github.com/silviazuffi/smalst">Three-D Safari: Learning to Estimate Zebra Pose, Shape, and Texture from Images "In the Wild". ICCV 2019.</a><br>
</p>
</div> -->
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