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<meta name="description" content="Market-1501 is a dataset is collection of CCTV footage from ..." />
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<div class='site_name'>MegaPixels</div>
<div class='splash'>Market 1501</div>
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<a href="/datasets/">Datasets</a>
<a href="/about/">About</a>
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<div class="content content-dataset">
<section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/market_1501/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span class="dataset-name">Market-1501</span> is a dataset is collection of CCTV footage from ...</span></div><div class='hero_subdesc'><span class='bgpad'>The Market-1501 dataset includes ...
</span></div></div></section><section><div class='left-sidebar'><div class='meta'>
<div class='gray'>Published</div>
<div>2015</div>
</div><div class='meta'>
<div class='gray'>Images</div>
<div>32,668 </div>
</div><div class='meta'>
<div class='gray'>Identities</div>
<div>1,501 </div>
</div><div class='meta'>
<div class='gray'>Purpose</div>
<div>Person re-identification</div>
</div><div class='meta'>
<div class='gray'>Website</div>
<div><a href='http://www.liangzheng.org/Project/project_reid.html' target='_blank' rel='nofollow noopener'>liangzheng.org</a></div>
</div><div class='meta'><div><div class='gray'>Collected</div><div>TBD</div></div><div><div class='gray'>Published</div><div>TBD</div></div><div><div class='gray'>Images</div><div>TBD</div></div><div><div class='gray'>Faces</div><div>TBD</div></div></div></div><h2>Market-1501 ...</h2>
<p>(PAGE UNDER DEVELOPMENT)</p>
</section><section>
<h3>Biometric Trade Routes</h3>
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<h3>Legend</h3>
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<li><span style="color: #f2f293">■</span> Industry</li>
<li><span style="color: #f30000">■</span> Academic</li>
<li><span style="color: #3264f6">■</span> Government</li>
</ul>
</div>
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<p>
To help understand how Market 1501 has been used around the world for commercial, military and academic research; publicly available research citing Market 1501 Dataset is collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location.
</p>
</section>
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</section>
<div class="caption">
<ul class="map-legend">
<li class="edu">Academic</li>
<li class="com">Commercial</li>
<li class="gov">Military / Government</li>
<li class="source">Citation data is collected using <a href="https://semanticscholar.org" target="_blank">SemanticScholar.org</a> then dataset usage verified and geolocated.</li>
</ul>
</div>
<!-- <section>
<p class='subp'>
[section under development] Market 1501 ... Standardized paragraph of text about the map. Sed ut perspiciatis, unde omnis iste natus error sit voluptatem accusantium doloremque laudantium, totam rem aperiam eaque ipsa, quae ab illo inventore veritatis et quasi architecto beatae vitae dicta sunt, explicabo.
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<h3>Supplementary Information</h3>
</section><section class="applet_container">
<h3>Dataset Citations</h3>
<p>
The dataset citations used in the visualizations were collected from <a href="https://www.semanticscholar.org">Semantic Scholar</a>, a website which aggregates and indexes research papers. Each citation was geocoded using names of institutions found in the PDF front matter, or as listed on other resources. These papers have been manually verified to show that researchers downloaded and used the dataset to train or test machine learning algorithms.
</p>
<div class="applet" data-payload="{"command": "citations"}"></div>
</section><section><h2>Research Notes</h2>
<ul>
<li>"MARS is an extension of the Market-1501 dataset. During collection, we placed six near synchronized cameras in the campus of Tsinghua university. There were Five 1,080<em>1920 HD cameras and one 640</em>480 SD camera. MARS consists of 1,261 different pedestrians whom are captured by at least 2 cameras. Given a query tracklet, MARS aims to retrieve tracklets that contain the same ID." - main paper</li>
<li>bbox "0065C1T0002F0016.jpg", "0065" is the ID of the pedestrian. "C1" denotes the first
camera (there are totally 6 cameras). "T0002" means the 2th tracklet. "F016" is the 16th frame
within this tracklet. For the tracklets, their names are accumulated for each ID; but for frames,
they start from "F001" in each tracklet.</li>
</ul>
<p>@proceedings{zheng2016mars,
title={MARS: A Video Benchmark for Large-Scale Person Re-identification},
author={Zheng, Liang and Bie, Zhi and Sun, Yifan and Wang, Jingdong and Su, Chi and Wang, Shengjin and Tian, Qi},
booktitle={European Conference on Computer Vision},
year={2016},
organization={Springer}
}</p>
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