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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="MS Celeb is a dataset of web images used for training and evaluating face recognition algorithms" />
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<div class='site_name'>MegaPixels</div>
<div class='splash'>Microsoft Celeb</div>
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<a href="/about/">About</a>
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<section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/msceleb/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'>MS Celeb is a dataset of web images used for training and evaluating face recognition algorithms</span></div><div class='hero_subdesc'><span class='bgpad'>The MS Celeb dataset includes over 10,000,000 images and 93,000 identities of semi-public figures collected using the Bing search engine
</span></div></div></section><section><h2>Microsoft Celeb Dataset (MS Celeb)</h2>
</section><section><div class='meta'>
<div class='gray'>Published</div>
<div>2016</div>
</div><div class='meta'>
<div class='gray'>Images</div>
<div>1,000,000 </div>
</div><div class='meta'>
<div class='gray'>Identities</div>
<div>100,000 </div>
</div><div class='meta'>
<div class='gray'>Purpose</div>
<div>Large-scale face recognition</div>
</div><div class='meta'>
<div class='gray'>Created by</div>
<div>Microsoft Research</div>
</div><div class='meta'>
<div class='gray'>Funded by</div>
<div>Microsoft Research</div>
</div><div class='meta'>
<div class='gray'>Website</div>
<div><a href='http://www.msceleb.org/' target='_blank' rel='nofollow noopener'>msceleb.org</a></div>
</div><p>[ PAGE UNDER DEVELOPMENT ]</p>
<p><a href="https://www.hrw.org/news/2019/01/15/letter-microsoft-face-surveillance-technology">https://www.hrw.org/news/2019/01/15/letter-microsoft-face-surveillance-technology</a></p>
<p><a href="https://www.scmp.com/tech/science-research/article/3005733/what-you-need-know-about-sensenets-facial-recognition-firm">https://www.scmp.com/tech/science-research/article/3005733/what-you-need-know-about-sensenets-facial-recognition-firm</a></p>
<p>{% include 'dashboard.html' %}</p>
<p>{% include 'supplementary_header.html' %}</p>
<h3>Additional Information</h3>
<ul>
<li>The dataset author spoke about his research at the CVPR conference in 2016 <a href="https://www.youtube.com/watch?v=Nl2fBKxwusQ">https://www.youtube.com/watch?v=Nl2fBKxwusQ</a></li>
</ul>
</section><section><h3>References</h3><section><ul class="footnotes"><li><a name="[^readme]" class="footnote_shim"></a><span class="backlinks"></span><p>"readme.txt" <a href="https://exhibits.stanford.edu/data/catalog/sx925dc9385">https://exhibits.stanford.edu/data/catalog/sx925dc9385</a>.</p>
</li><li><a name="[^localized_region_context]" class="footnote_shim"></a><span class="backlinks"></span><p>Li, Y. and Dou, Y. and Liu, X. and Li, T. Localized Region Context and Object Feature Fusion for People Head Detection. ICIP16 Proceedings. 2016. Pages 594-598.</p>
</li><li><a name="[^replacement_algorithm]" class="footnote_shim"></a><span class="backlinks"></span><p>Zhao. X, Wang Y, Dou, Y. A Replacement Algorithm of Non-Maximum Suppression Base on Graph Clustering.</p>
</li></ul></section></section>
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