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<section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/viper/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span style='color: #ffaa00'>VIPeR</span> is a person re-identification dataset of images captured at UC Santa Cruz in 2007</span></div><div class='hero_subdesc'><span class='bgpad'>VIPeR contains 1,264 images and 632 persons on the UC Santa Cruz campus and is used to train person re-identification algorithms for surveillance
</span></div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Published</div><div>2007</div></div><div><div class='gray'>Images</div><div>1,264</div></div><div><div class='gray'>Persons</div><div>632</div></div><div><div class='gray'>Created by</div><div>UC Santa Cruz</div></div></div></div><h2>VIPeR Dataset</h2>
<p>(PAGE UNDER DEVELOPMENT)</p>
<p><em>VIPeR (Viewpoint Invariant Pedestrian Recognition)</em> is a dataset of pedestrian images captured at University of California Santa Cruz in 2007. Accoriding to the reserachers 2 "cameras were placed in different locations in an academic setting and subjects were notified of the presence of cameras, but were not coached or instructed in any way."</p>
<p>VIPeR is amongst the most widely used publicly available person re-identification datasets. In 2017 the VIPeR dataset was combined into a larger person re-identification created by the Chinese University of Hong Kong called PETA (PEdesTrian Attribute).</p>
</section><section>
<h3>Who used VIPeR?</h3>
<p>
This bar chart presents a ranking of the top countries where citations originated. Mouse over individual columns
to see yearly totals. Colors are only assigned to the top 10 overall countries.
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<h3>Biometric Trade Routes (beta)</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>
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<p>
To understand how VIPeR 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 not yet manually verified.
</div>
<section>
<p class='subp'>
The data is generated by collecting all citations for all original research papers associated with the dataset. Then the PDFs are then converted to text and the organization names are extracted and geocoded. Because of the automated approach to extracting data, actual use of the dataset can not yet be confirmed. This visualization is provided to help locate and confirm usage and will be updated as data noise is reduced.
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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. Metadata was extracted from these papers, including extracting names of institutions automatically from PDFs, and then the addresses were geocoded. Data is not yet manually verified, and reflects anytime the paper was cited. Some papers may only mention the dataset in passing, while others use it as part of their research methodology.
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