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<!doctype html>
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<title>MegaPixels</title>
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<meta name="author" content="Adam Harvey" />
<meta name="description" content="Market-1501 is a dataset is collection of CCTV footage from ..." />
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<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><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>Information Supply Chain</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>
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<p>
To understand how Market 1501 has been used around the world...
affected global research on computer vision, surveillance, defense, and consumer technology, the and where this dataset has been used the locations of each organization that used or referenced the datast
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<div class="map-legend-item edu">Academic</div>
<div class="map-legend-item com">Industry</div>
<div class="map-legend-item gov">Government</div>
Data is compiled from <a href="https://www.semanticscholar.org">Semantic Scholar</a> and has been manually verified to show usage of Market 1501.
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<h2>Supplementary Information</h2>
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<h3>Citations</h3>
<p>
Citations were collected from <a href="https://www.semanticscholar.org">Semantic Scholar</a>, a website which aggregates
and indexes research papers. The citations were 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 and/or test machine learning algorithms.
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</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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