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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="COFW: Caltech Occluded Faces in The Wild" />
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<div class='site_name'>MegaPixels</div>
<div class='splash'>COFW Dataset</div>
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<a href="/datasets/">Datasets</a>
<a href="/about/">About</a>
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</header>
<div class="content content-">
<section><h2>Caltech Occluded Faces in the Wild</h2>
</section><section><div class='right-sidebar'><div class='meta'>
<div class='gray'>Published</div>
<div>2013</div>
</div><div class='meta'>
<div class='gray'>Images</div>
<div>1,007 </div>
</div><div class='meta'>
<div class='gray'>Purpose</div>
<div>challenging dataset (sunglasses, hats, interaction with objects)</div>
</div><div class='meta'>
<div class='gray'>Website</div>
<div><a href='http://www.vision.caltech.edu/xpburgos/ICCV13/' target='_blank' rel='nofollow noopener'>caltech.edu</a></div>
</div></div><p>[ PAGE UNDER DEVELOPMENT ]</p>
</section><section>
<h3>Who used COFW Dataset?</h3>
<p>
This bar chart presents a ranking of the top countries where dataset citations originated. Mouse over individual columns to see yearly totals. These charts show at most the top 10 countries.
</p>
</section>
<section class="applet_container">
<!-- <div style="position: absolute;top: 0px;right: -55px;width: 180px;font-size: 14px;">Labeled Faces in the Wild Dataset<br><span class="numc" style="font-size: 11px;">20 citations</span>
</div> -->
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</section>
<section class="applet_container">
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</section>
<section>
<h3>Biometric Trade Routes</h3>
<p>
To help understand how COFW Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Caltech Occluded Faces in the Wild was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal research projects at that location.
</p>
</section>
<section class="applet_container fullwidth">
<div class="applet" data-payload="{"command": "map"}"></div>
</section>
<div class="caption">
<ul class="map-legend">
<li class="edu">Academic</li>
<li class="com">Commercial</li>
<li class="gov">Military / Government</li>
</ul>
<div class="source">Citation data is collected using <a href="https://semanticscholar.org" target="_blank">SemanticScholar.org</a> then dataset usage verified and geolocated.</div >
</div>
<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><h3>(ignore) research notes</h3>
</section><section><div class='meta'><div><div class='gray'>Years</div><div>1993-1996</div></div><div><div class='gray'>Images</div><div>14,126</div></div><div><div class='gray'>Identities</div><div>1,199 </div></div><div><div class='gray'>Origin</div><div>Web Searches</div></div><div><div class='gray'>Funded by</div><div>ODNI, IARPA, Microsoft</div></div></div><section><section><p>COFW is "is designed to benchmark face landmark algorithms in realistic conditions, which include heavy occlusions and large shape variations" [Robust face landmark estimation under occlusion].</p>
<blockquote><p>We asked four people with different levels of computer vision knowledge to each collect 250 faces representative of typical real-world images, with the clear goal of challenging computer vision methods.
The result is 1,007 images of faces obtained from a variety of sources.</p>
</blockquote>
<p>Robust face landmark estimation under occlusion</p>
<blockquote><p>Our face dataset is designed to present faces in real-world conditions. Faces show large variations in shape and occlusions due to differences in pose, expression, use of accessories such as sunglasses and hats and interactions with objects (e.g. food, hands, microphones, etc.). All images were hand annotated in our lab using the same 29 landmarks as in LFPW. We annotated both the landmark positions as well as their occluded/unoccluded state. The faces are occluded to different degrees, with large variations in the type of occlusions encountered. COFW has an average occlusion of over 23%.
To increase the number of training images, and since COFW has the exact same landmarks as LFPW, for training we use the original non-augmented 845 LFPW faces + 500 COFW faces (1345 total), and for testing the remaining 507 COFW faces. To make sure all images had occlusion labels, we annotated occlusion on the available 845 LFPW training images, finding an average of only 2% occlusion.</p>
</blockquote>
<p><a href="http://www.vision.caltech.edu/xpburgos/ICCV13/">http://www.vision.caltech.edu/xpburgos/ICCV13/</a></p>
<blockquote><p>This research is supported by NSF Grant 0954083 and by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via IARPA R&D Contract No. 2014-14071600012.</p>
</blockquote>
<p><a href="https://www.cs.cmu.edu/~peiyunh/topdown/">https://www.cs.cmu.edu/~peiyunh/topdown/</a></p>
</section><section>
<h3>Biometric Trade Routes</h3>
<p>
To help understand how COFW Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Caltech Occluded Faces in the Wild was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the location markers to reveal research projects at that location.
</p>
</section>
<section class="applet_container fullwidth">
<div class="applet" data-payload="{"command": "map"}"></div>
</section>
<div class="caption">
<ul class="map-legend">
<li class="edu">Academic</li>
<li class="com">Commercial</li>
<li class="gov">Military / Government</li>
</ul>
<div class="source">Citation data is collected using <a href="https://semanticscholar.org" target="_blank">SemanticScholar.org</a> and then dataset usage verified and geolocated.</div >
</div><section>
<div class="hr-wave-holder">
<div class="hr-wave-line hr-wave-line1"></div>
<div class="hr-wave-line hr-wave-line2"></div>
</div>
<h2>Supplementary Information</h2>
</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>
<h3>Who used COFW Dataset?</h3>
<p>
This bar chart presents a ranking of the top countries where dataset citations originated. Mouse over individual columns to see yearly totals. These charts show at most the top 10 countries.
</p>
</section>
<section class="applet_container">
<!-- <div style="position: absolute;top: 0px;right: -55px;width: 180px;font-size: 14px;">Labeled Faces in the Wild Dataset<br><span class="numc" style="font-size: 11px;">20 citations</span>
</div> -->
<div class="applet" data-payload="{"command": "chart"}"></div>
</section><section><p>TODO</p>
<h2>- replace graphic</h2>
</section>
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