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diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html index b4923877..d451d0cd 100644 --- a/site/public/datasets/lfw/index.html +++ b/site/public/datasets/lfw/index.html @@ -8,7 +8,6 @@ <meta name="referrer" content="no-referrer" /> <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" /> <link rel='stylesheet' href='/assets/css/fonts.css' /> - <link rel='stylesheet' href='/assets/css/tabulator.css' /> <link rel='stylesheet' href='/assets/css/css.css' /> <link rel='stylesheet' href='/assets/css/leaflet.css' /> <link rel='stylesheet' href='/assets/css/applets.css' /> @@ -18,6 +17,7 @@ <a class='slogan' href="/"> <div class='logo'></div> <div class='site_name'>MegaPixels</div> + <div class='splash'>LFW</div> </a> <div class='links'> <a href="/datasets/">Datasets</a> @@ -27,7 +27,22 @@ <div class="content content-"> <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span class="dataset-name">Labeled Faces in The Wild (LFW)</span> is the first facial recognition dataset created entirely from online photos</span></div><div class='hero_subdesc'><span class='bgpad'>It includes 13,456 images of 4,432 people's images copied from the Internet during 2002-2004 and is the most frequently used dataset in the world for benchmarking face recognition algorithms. -</span></div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Created</div><div>2002 – 2004</div></div><div><div class='gray'>Images</div><div>13,233</div></div><div><div class='gray'>Identities</div><div>5,749</div></div><div><div class='gray'>Origin</div><div>Yahoo! News Images</div></div><div><div class='gray'>Used by</div><div>Facebook, Google, Microsoft, Baidu, Tencent, SenseTime, Face++, CIA, NSA, IARPA</div></div><div><div class='gray'>Website</div><div><a href="http://vis-www.cs.umass.edu/lfw">umass.edu</a></div></div></div><ul> +</span></div></div></section><section><div class='left-sidebar'><div class='meta'> + <div class='gray'>Published</div> + <div>2007</div> + </div><div class='meta'> + <div class='gray'>Images</div> + <div>13,233 </div> + </div><div class='meta'> + <div class='gray'>Identities</div> + <div>5,749 </div> + </div><div class='meta'> + <div class='gray'>Purpose</div> + <div>face recognition</div> + </div><div class='meta'> + <div class='gray'>Website</div> + <div><a href='http://vis-www.cs.umass.edu/lfw/' target='_blank' rel='nofollow noopener'>umass.edu</a></div> + </div><div class='meta'><div><div class='gray'>Created</div><div>2002 – 2004</div></div><div><div class='gray'>Images</div><div>13,233</div></div><div><div class='gray'>Identities</div><div>5,749</div></div><div><div class='gray'>Origin</div><div>Yahoo! News Images</div></div><div><div class='gray'>Used by</div><div>Facebook, Google, Microsoft, Baidu, Tencent, SenseTime, Face++, CIA, NSA, IARPA</div></div><div><div class='gray'>Website</div><div><a href="http://vis-www.cs.umass.edu/lfw">umass.edu</a></div></div></div><ul> <li>There are about 3 men for every 1 woman in the LFW dataset<a class="footnote_shim" name="[^lfw_www]_1"> </a><a href="#[^lfw_www]" class="footnote" title="Footnote 1">1</a></li> <li>The person with the most images is <a href="http://vis-www.cs.umass.edu/lfw/person/George_W_Bush_comp.html">George W. Bush</a> with 530</li> <li>There are about 3 George W. Bush's for every 1 <a href="http://vis-www.cs.umass.edu/lfw/person/Tony_Blair.html">Tony Blair</a></li> @@ -46,7 +61,7 @@ <p>The <em>Names and Faces</em> dataset was the first face recognition dataset created entire from online photos. However, <em>Names and Faces</em> and <em>LFW</em> are not the first face recognition dataset created entirely "in the wild". That title belongs to the <a href="/datasets/ucd_faces/">UCD dataset</a>. Images obtained "in the wild" means using an image without explicit consent or awareness from the subject or photographer.</p> </section><section> - <h3>Information Supply Chain</h3> + <h3>Biometric Trade Routes</h3> <!-- <div class="map-sidebar right-sidebar"> <h3>Legend</h3> @@ -58,66 +73,59 @@ </div> --> <p> - To understand how LFW 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 + To help understand how LFW has been used around the world for commercial, military and academic research; publicly available research citing Labeled Faces in the Wild 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> -<section class="applet_container"> +<section class="applet_container fullwidth"> <div class="applet" data-payload="{"command": "map"}"></div> + </section> <div class="caption"> - <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 LFW. + <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> +<!-- <section> <p class='subp'> - 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. + [section under development] LFW ... 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. </p> -</section><section> +</section> + --><section> <h3>Who used LFW?</h3> <p> - This bar chart presents a ranking of the top countries where citations originated. Mouse over individual columns - to see yearly totals. These charts show at most the top 10 countries. + 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> - These pie charts show overall totals based on country and institution type. - </p> - - </section> - -<section class="applet_container"> +</section><section class="applet_container"> <div class="applet" data-payload="{"command": "piechart"}"></div> </section><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> + <h3>Supplementary Information</h3> + </section><section class="applet_container"> - <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. - </p> + <h3>Dataset Citations</h3> <p> - Add button/link to download CSV + 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> |