Merge branch 'master' of github.com:adamhrv/megapixels_dev

7 files changed, 15 insertions, 45 deletions

diff --git a/site/public/datasets/50_people_one_question/index.html b/site/public/datasets/50_people_one_question/index.html
index 25df92b9..3a854d50 100644
--- a/site/public/datasets/50_people_one_question/index.html
+++ b/site/public/datasets/50_people_one_question/index.html
@@ -28,6 +28,7 @@
     
   <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/50_people_one_question/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span style="color:#ffaa00">People One Question</span> is a dataset of people from an online video series on YouTube and Vimeo used for building facial recogntion algorithms</span></div><div class='hero_subdesc'><span class='bgpad'>People One Question 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>50 People 1 Question</h2>
+<p>(PAGE UNDER DEVELOPMENT)</p>
 <p>At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio.</p>
 <p>Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat</p>
 </section><section>
diff --git a/site/public/datasets/brainwash/index.html b/site/public/datasets/brainwash/index.html
index e5c9da79..ab002c78 100644
--- a/site/public/datasets/brainwash/index.html
+++ b/site/public/datasets/brainwash/index.html
@@ -4,7 +4,7 @@
   <title>MegaPixels</title>
   <meta charset="utf-8" />
   <meta name="author" content="Adam Harvey" />
-  <meta name="description" content="Brainwash is a dataset of people from webcams the Brainwash Cafe in San Francisco being used to train face detection algorithms" />
+  <meta name="description" content="Brainwash is a dataset of webcam images from the Brainwash Cafe in San Francisco" />
   <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' />
@@ -26,8 +26,9 @@
   </header>
   <div class="content content-dataset">
     
-  <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span style='color: #ffaa00'>Brainwash</span> is a dataset of people from webcams the Brainwash Cafe in San Francisco being used to train face detection algorithms</span></div><div class='hero_subdesc'><span class='bgpad'>Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe"
+  <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span style='color: #ffaa00'>Brainwash</span> is a dataset of webcam images from the Brainwash Cafe in San Francisco</span></div><div class='hero_subdesc'><span class='bgpad'>The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection algorithms
 </span></div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Collected</div><div>2014</div></div><div><div class='gray'>Published</div><div>2015</div></div><div><div class='gray'>Images</div><div>11,918</div></div><div><div class='gray'>Faces</div><div>91,146</div></div><div><div class='gray'>Created by</div><div>Stanford Department of Computer Science</div></div><div><div class='gray'>Funded by</div><div>Max Planck Center for Visual Computing and Communication</div></div><div><div class='gray'>Resolution</div><div>640x480px</div></div><div><div class='gray'>Size</div><div>4.1GB</div></div><div><div class='gray'>Origin</div><div>Brainwash Cafe, San Franscisco</div></div><div><div class='gray'>Purpose</div><div>Training face detection</div></div><div><div class='gray'>Website</div><div><a href="https://exhibits.stanford.edu/data/catalog/sx925dc9385">stanford.edu</a></div></div><div><div class='gray'>Paper</div><div><a href="http://arxiv.org/abs/1506.04878">End-to-End People Detection in Crowded Scenes</a></div></div></div></div><h2>Brainwash Dataset</h2>
+<p>(PAGE UNDER DEVELOPMENT)</p>
 <p><em>Brainwash</em> is a face detection dataset created from the Brainwash Cafe's livecam footage including 11,918 images of "everyday life of a busy downtown cafe<a class="footnote_shim" name="[^readme]_1"> </a><a href="#[^readme]" class="footnote" title="Footnote 1">1</a>". The images are used to develop face detection algorithms for the "challenging task of detecting people in crowded scenes" and tracking them.</p>
 <p>Before closing in 2017, Brainwash Cafe was a "cafe and laundromat" located in San Francisco's SoMA district. The cafe published a publicy available livestream from the cafe with a view of the cash register, performance stage, and seating area.</p>
 <p>Since it's publication by Stanford in 2015, the Brainwash dataset has appeared in several notable research papers. In September 2016 four researchers from the National University of Defense Technology in Changsha, China used the Brainwash dataset for a research study on "people head detection in crowded scenes", concluding that their algorithm "achieves superior head detection performance on the crowded scenes dataset<a class="footnote_shim" name="[^localized_region_context]_1"> </a><a href="#[^localized_region_context]" class="footnote" title="Footnote 2">2</a>". And again in 2017 three researchers at the National University of Defense Technology used Brainwash for a study on object detection noting "the data set used in our experiment is shown in Table 1, which includes one scene of the brainwash dataset<a class="footnote_shim" name="[^replacement_algorithm]_1"> </a><a href="#[^replacement_algorithm]" class="footnote" title="Footnote 3">3</a>".</p>
diff --git a/site/public/datasets/celeba/index.html b/site/public/datasets/celeba/index.html
index 2977cf2a..024f842f 100644
--- a/site/public/datasets/celeba/index.html
+++ b/site/public/datasets/celeba/index.html
@@ -28,6 +28,7 @@
     
   <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/celeba/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span style="color:#ffaa00">CelebA</span> is a dataset of people...</span></div><div class='hero_subdesc'><span class='bgpad'>CelebA 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>CelebA</h2>
+<p>(PAGE UNDER DEVELOPMENT)</p>
 <p>At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio.</p>
 <p>Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat</p>
 </section><section>
diff --git a/site/public/datasets/cofw/index.html b/site/public/datasets/cofw/index.html
index 8410559f..605a325a 100644
--- a/site/public/datasets/cofw/index.html
+++ b/site/public/datasets/cofw/index.html
@@ -26,8 +26,9 @@
   </header>
   <div class="content content-">
     
-  <section><h1>Caltech Occluded Faces in The Wild</h1>
-</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><!--header--></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/cofw/assets/cofw_index.gif' alt=''></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>
+  <section><div class='left-sidebar'><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></div><h2>Caltech Occluded Faces in the Wild</h2>
+<p>(PAGE UNDER DEVELOPMENT)</p>
+<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>
 <p>RESEARCH below this line</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>
diff --git a/site/public/datasets/index.html b/site/public/datasets/index.html
index ab9f852d..d9452b11 100644
--- a/site/public/datasets/index.html
+++ b/site/public/datasets/index.html
@@ -37,18 +37,6 @@
 
     <div class="dataset-list">
     
-      <a href="/datasets/50_people_one_question/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/50_people_one_question/assets/index.jpg)">
-        <div class="dataset">
-          <span class='title'>50 People One Question</span>
-          <div class='fields'>
-            <div class='year visible'><span>2013</span></div>
-            <div class='purpose'><span>facial landmark estimation in the wild</span></div>
-            <div class='images'><span> images</span></div>
-            <div class='identities'><span></span></div>
-          </div>
-        </div>
-      </a>
-    
       <a href="/datasets/brainwash/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/index.jpg)">
         <div class="dataset">
           <span class='title'>Brainwash</span>
@@ -61,30 +49,6 @@
         </div>
       </a>
     
-      <a href="/datasets/celeba/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/celeba/assets/index.jpg)">
-        <div class="dataset">
-          <span class='title'>CelebA</span>
-          <div class='fields'>
-            <div class='year visible'><span>2015</span></div>
-            <div class='purpose'><span>face attribute recognition, face detection, and landmark (or facial part) localization</span></div>
-            <div class='images'><span>202,599  images</span></div>
-            <div class='identities'><span>10,177 </span></div>
-          </div>
-        </div>
-      </a>
-    
-      <a href="/datasets/cofw/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/cofw/assets/index.jpg)">
-        <div class="dataset">
-          <span class='title'>Caltech Occluded Faces in The Wild</span>
-          <div class='fields'>
-            <div class='year visible'><span>2013</span></div>
-            <div class='purpose'><span>challenging dataset (sunglasses, hats, interaction with objects), supported by IARPA</span></div>
-            <div class='images'><span>1,007  images</span></div>
-            <div class='identities'><span></span></div>
-          </div>
-        </div>
-      </a>
-    
       <a href="/datasets/lfw/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/index.jpg)">
         <div class="dataset">
           <span class='title'>Labeled Faces in The Wild</span>
diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html
index 814cd167..477673e2 100644
--- a/site/public/datasets/lfw/index.html
+++ b/site/public/datasets/lfw/index.html
@@ -4,7 +4,7 @@
   <title>MegaPixels</title>
   <meta charset="utf-8" />
   <meta name="author" content="Adam Harvey" />
-  <meta name="description" content="Labeled Faces in The Wild (LFW) is a database of face photographs designed for studying the problem of unconstrained face recognition." />
+  <meta name="description" content="Labeled Faces in The Wild (LFW) is the first facial recognition dataset created entirely from online photos" />
   <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' />
@@ -26,7 +26,7 @@
   </header>
   <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 style='color: #ff0000'>Labeled Faces in The Wild</span> (LFW) is a database of face photographs designed for studying the problem of unconstrained face recognition.</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.
+  <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 style='color: #ff0000'>Labeled Faces in The Wild</span> (LFW) 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 &ndash; 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>
@@ -37,6 +37,7 @@
 <li>* denotes partial funding for related research</li>
 </ul>
 </div><h2>Labeled Faces in the Wild</h2>
+<p>(PAGE UNDER DEVELOPMENT)</p>
 <p><em>Labeled Faces in The Wild</em> (LFW) is "a database of face photographs designed for studying the problem of unconstrained face recognition<a class="footnote_shim" name="[^lfw_www]_2"> </a><a href="#[^lfw_www]" class="footnote" title="Footnote 1">1</a>. It is used to evaluate and improve the performance of facial recognition algorithms in academic, commercial, and government research. According to BiometricUpdate.com<a class="footnote_shim" name="[^lfw_pingan]_1"> </a><a href="#[^lfw_pingan]" class="footnote" title="Footnote 3">3</a>, LFW is "the most widely used evaluation set in the field of facial recognition, LFW attracts a few dozen teams from around the globe including Google, Facebook, Microsoft Research Asia, Baidu, Tencent, SenseTime, Face++ and Chinese University of Hong Kong."</p>
 <p>The LFW dataset includes 13,233 images of 5,749 people that were collected between 2002-2004. LFW is a subset of <em>Names of Faces</em> and is part of the first facial recognition training dataset created entirely from images appearing on the Internet. The people appearing in LFW are...</p>
 <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>
diff --git a/site/public/datasets/mars/index.html b/site/public/datasets/mars/index.html
index 66084e15..bfad52a3 100644
--- a/site/public/datasets/mars/index.html
+++ b/site/public/datasets/mars/index.html
@@ -4,7 +4,7 @@
   <title>MegaPixels</title>
   <meta charset="utf-8" />
   <meta name="author" content="Adam Harvey" />
-  <meta name="description" content="MARS is a dataset of people..." />
+  <meta name="description" content="The Motion Analysis and Re-identification Set (MARS) is a dataset is collection of CCTV footage " />
   <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' />
@@ -26,8 +26,9 @@
   </header>
   <div class="content content-dataset">
     
-  <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/mars/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span style="color:#ffaa00">MARS</span> is a dataset of people...</span></div><div class='hero_subdesc'><span class='bgpad'>MARS 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>50 MARS</h2>
+  <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/mars/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'>The <span style="color:#99ccee">Motion Analysis and Re-identification Set (MARS)</span> is a dataset is collection of CCTV footage </span></div><div class='hero_subdesc'><span class='bgpad'>The MARS dataset includes 1,191,003 of people used for training person re-identification algorithms
+</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>Motion Analysis and Re-identification Set (MARS)</h2>
+<p>(PAGE UNDER DEVELOPMENT)</p>
 <p>At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio.</p>
 <p>Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat</p>
 </section><section>