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Added first draft of project page.
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@AndreasAZiegler
AndreasAZiegler committed Mar 4, 2024
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<script src="http://www.google.com/jsapi" type="text/javascript"></script>
<script type="text/javascript">google.load("jquery", "1.3.2");</script>

<style type="text/css">
body {
font-family: "HelveticaNeue-Light", "Helvetica Neue Light", "Helvetica Neue", Helvetica, Arial, "Lucida Grande", sans-serif;
font-weight: 300;
font-size: 18px;
margin-left: auto;
margin-right: auto;
width: 1100px;
}

h1 {
font-size: 32px;
font-weight: 300;
}

.disclaimerbox {
background-color: #eee;
border: 1px solid #eeeeee;
border-radius: 10px;
-moz-border-radius: 10px;
-webkit-border-radius: 10px;
padding: 20px;
}

video.header-vid {
height: 140px;
border: 1px solid black;
border-radius: 10px;
-moz-border-radius: 10px;
-webkit-border-radius: 10px;
}

img.header-img {
height: 140px;
border: 1px solid black;
border-radius: 10px;
-moz-border-radius: 10px;
-webkit-border-radius: 10px;
}

img.rounded {
border: 1px solid #eeeeee;
border-radius: 10px;
-moz-border-radius: 10px;
-webkit-border-radius: 10px;
}

a:link,
a:visited {
color: #1367a7;
text-decoration: none;
}

a:hover {
color: #208799;
}

td.dl-link {
height: 160px;
text-align: center;
font-size: 22px;
}

.layered-paper-big {
/* modified from: http://css-tricks.com/snippets/css/layered-paper/ */
box-shadow:
0px 0px 1px 1px rgba(0, 0, 0, 0.35),
/* The top layer shadow */
5px 5px 0 0px #fff,
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/* The fifth layer shadow */
margin-left: 10px;
margin-right: 45px;
}

.paper-big {
/* modified from: http://css-tricks.com/snippets/css/layered-paper/ */
box-shadow:
0px 0px 1px 1px rgba(0, 0, 0, 0.35);
/* The top layer shadow */

margin-left: 10px;
margin-right: 45px;
}


.layered-paper {
/* modified from: http://css-tricks.com/snippets/css/layered-paper/ */
box-shadow:
0px 0px 1px 1px rgba(0, 0, 0, 0.35),
/* The top layer shadow */
5px 5px 0 0px #fff,
/* The second layer */
5px 5px 1px 1px rgba(0, 0, 0, 0.35),
/* The second layer shadow */
10px 10px 0 0px #fff,
/* The third layer */
10px 10px 1px 1px rgba(0, 0, 0, 0.35);
/* The third layer shadow */
margin-top: 5px;
margin-left: 10px;
margin-right: 30px;
margin-bottom: 5px;
}

.vert-cent {
position: relative;
top: 50%;
transform: translateY(-50%);
}

hr {
border: 0;
height: 1px;
background-image: linear-gradient(to right, rgba(0, 0, 0, 0), rgba(0, 0, 0, 0.75), rgba(0, 0, 0, 0));
}
</style>

<html>

<head>
<title>Spiking Neural Networks for Fast-Moving Object Detection on Neuromorphic Hardware Devices Using an Event-Based Camera</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="Spiking Neural Networks for Fast-Moving Object Detection on Neuromorphic Hardware Devices Using an Event-Based Camera" />
<meta property="og:description" content="Paper description." />

<!-- Get from Google Analytics -->
<!-- Global site tag (gtag.js) - Google Analytics -->
<script async src=""></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag() {dataLayer.push(arguments);}
gtag('js', new Date());

gtag('config', 'UA-75863369-6');
</script>
</head>

<body>
<br>
<center>
<span style="font-size:36px">Spiking Neural Networks for Fast-Moving Object Detection on Neuromorphic Hardware Devices Using an Event-Based Camera</span>
<table align=center width=990px>
<table align=center width=990px>
<tr>
<td align=center width=110px>
<center>
<span style="font-size:24px"><a href="https://andreasaziegler.github.io/">Andreas Ziegler</a></span>
</center>
</td>
<td align=center width=110px>
<center>
<span style="font-size:24px">Karl Vetter</span>
</center>
</td>
<td align=center width=110px>
<center>
<span style="font-size:24px"><a href="https://uni-tuebingen.de/de/226101">Thomas Gossard</a></span>
</center>
</td>
<td align=center width=100px>
<center>
<span style="font-size:24px"><a href="https://uni-tuebingen.de/de/138688">Jonas Tebbe</a></span>
</center>
</td>
<td align=center width=100px>
<center>
<span style="font-size:24px"><a href="https://uni-tuebingen.de/de/138703">Andreas Zell</a></span>
</center>
</td>
</tr>
</table>
<!--<table align=center width=990px>
<span style="font-size:24px">*equal contribution</span>
</table>-->
<table align=center width=250px>
<tr>
<td align=center width=120px>
<center>
<span style="font-size:24px"><a href=''>[Paper]</a></span>
</center>
</td>
<td align=center width=120px>
<center>
<span style="font-size:24px"><a href='https://github.com/cogsys-tuebingen/snn-edge-benchmark'> [Code]</a></span><br>
</center>
</td>
<td align=center width=120px>
<center>
<span style="font-size:24px"><a href='https://github.com/cogsys-tuebingen/snn-edge-benchmark'> [Dataset]</a></span><br>
</center>
</td>
</tr>
</table>
</table>
</center>

<center>
<table align=center width=850px>
<tr>
<td width=260px>
<center>
<img class="round" style="width:600px" src="./resources/teaser.png" />
</center>
</td>
</tr>
</table>
<table align=center width=850px>
<tr>
<td>
<center>
<i>Five observed 2D trajectories in the camera frame of the event-based camera with <font color="green">ground truth in green</font> and the <font color="red">estimated positions in red</font>.</i>
</center>
</td>
</tr>
</table>
</center>

<hr>

<table align=center width=850px>
<center>
<h1>Abstract</h1>
</center>
<tr>
<td>
Table tennis is a fast-paced and exhilarating sport that demands agility, precision, and fast reflexes. In recent years, robotic table tennis has become a popular research challenge for robot perception algorithms. Fast and accurate ball detection is crucial for enabling a robotic arm to rally the ball back successfully. Previous approaches have employed conventional frame-based cameras with CNN or traditional computer vision methods. In this paper, we propose a novel solution that combines an event-based camera with Spiking Neural Network (SNN) for ball detection. We use multiple state-of-the-art SNN frameworks and develop a SNN architecture for each of them, complying with their corresponding limitations. Additionally, we implement the SNN solution across multiple neuromorphic edge devices, conducting comparisons of their accuracies and run-times. This furnishes robotics researchers with a benchmark illustrating the capabilities achievable with each SNN framework and a corresponding neuromorphic edge device. Next to this comparison of SNN solutions for robots, we also show that an SNN on a neuromorphic edge device is able to run in real-time in a closed loop robotic system, a table tennis robot in our use case.
</td>
</tr>
</table>
<br>

<hr>
<center>
<h1>Talk</h1>
</center>
<p align="center">
<iframe width="660" height="395" src="https://www.youtube.com" frameborder="0"
allow="autoplay; encrypted-media" allowfullscreen align="center"></iframe>
</p>

<!--
<table align=center width=800px>
<br>
<tr>
<center>
<span style="font-size:28px"><a href=''>[Slides]</a>
</span>
</center>
</tr>
</table>
<hr>
-->

<!--
<center>
<h1>Code</h1>
</center>
<table align=center width=420px>
<center>
<tr>
<td>
</td>
</tr>
</center>
</table>
<table align=center width=400px>
<tr>
<td align=center width=400px>
<center>
<td><img class="round" style="width:450px" src="./resources/method_diagram.png" /></td>
</center>
</td>
</tr>
</table>
<table align=center width=850px>
<center>
<tr>
<td>
Short description if wanted
</td>
</tr>
</center>
</table>
<table align=center width=800px>
<br>
<tr>
<center>
<span style="font-size:28px">&nbsp;<a href='https://github.com/richzhang/webpage-template'>[GitHub]</a>
</center>
</span>
</table>
<br>
<hr>
-->

<table align=center width=450px>
<center>
<h1>Paper</h1>
</center>
<tr>
<td><a href=""><img class="layered-paper-big" style="height:175px" src="./resources/paper.png" /></a></td>
<td><span style="font-size:14pt">A. Ziegler, K. Vetter, T. Gossard, J. Tebbe, A. Zell.<br>
<b>Spiking Neural Networks for Fast-Moving Object Detection on Neuromorphic Hardware Devices Using an Event-Based Camera.</b><br>
<!--In Conference, 20XX.<br>-->
(hosted on <a href="">ArXiv</a>)<br>
<!-- (<a href="./resources/camera-ready.pdf">camera ready</a>)<br> -->
<span style="font-size:4pt"><a href=""><br></a>
</span>
</td>
</tr>
</table>
<br>

<table align=center width=600px>
<tr>
<td><span style="font-size:14pt">
<center>
<a href="./resources/bibtex.txt">[Bibtex]</a>
</center>
</td>
</tr>
</table>

<hr>
<br>

<table align=center width=900px>
<tr>
<td width=400px>
<left>
<center>
<h1>Acknowledgements</h1>
</center>
This research was partially funded by <a href="https://ai.sony">Sony AI</a>.
</left>
</td>
</tr>
</table>

<br>
</body>

</html>
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