diff options
| author | adamhrv <adam@ahprojects.com> | 2019-04-16 17:31:17 +0200 |
|---|---|---|
| committer | adamhrv <adam@ahprojects.com> | 2019-04-16 17:31:17 +0200 |
| commit | 391b945604a65f09da7d3f069dcef5a571e9b55c (patch) | |
| tree | ffa9812f46abcebd5f3b371be913b774d8bd123f /site | |
| parent | 776ae57da4a27966d58aa76bcac1eed67b75687b (diff) | |
| parent | 92cdcf6e684a2de2846865e99281d939cc3ecd5a (diff) | |
merge
Diffstat (limited to 'site')
41 files changed, 180 insertions, 1227 deletions
diff --git a/site/assets/css/css.css b/site/assets/css/css.css index 81a38487..492ec347 100644 --- a/site/assets/css/css.css +++ b/site/assets/css/css.css @@ -319,7 +319,8 @@ p.subp{ .right-sidebar { float: right; width: 240px; - margin: 75px 20px 20px 20px; + margin: 0px 20px 20px 20px; + padding-top: 12px; padding-left: 20px; border-left: 1px solid #333; font-family: 'Roboto'; diff --git a/site/content/pages/datasets/50_people_one_question/index.md b/site/content/pages/datasets/50_people_one_question/index.md index 09406f43..8b7fb931 100644 --- a/site/content/pages/datasets/50_people_one_question/index.md +++ b/site/content/pages/datasets/50_people_one_question/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## 50 People 1 Question + ### sidebar ### end sidebar -## 50 People 1 Question - [ page under development ] {% include 'dashboard.html' %}
\ No newline at end of file diff --git a/site/content/pages/datasets/afad/index.md b/site/content/pages/datasets/afad/index.md index c941cbc6..755506d8 100644 --- a/site/content/pages/datasets/afad/index.md +++ b/site/content/pages/datasets/afad/index.md @@ -10,11 +10,11 @@ authors: Adam Harvey ------------ +## Asian Face Age Dataset + ### sidebar ### end sidebar -## Asian Face Age Dataset - [ page under development ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md index 6bb7f287..156b02c7 100644 --- a/site/content/pages/datasets/brainwash/index.md +++ b/site/content/pages/datasets/brainwash/index.md @@ -14,11 +14,11 @@ authors: Adam Harvey ------------ +## Brainwash Dataset + ### sidebar ### end sidebar -## Brainwash Dataset - *Brainwash* is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 11,918 images of "everyday life of a busy downtown cafe"[^readme] captured at 100 second intervals throught the entire day. Brainwash dataset was captured during 3 days in 2014: October 27, November 13, and November 24. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com.[^end_to_end] Brainwash is not a widely used dataset but since its publication by Stanford University in 2015, it has notably appeared in several research papers from the National University of Defense Technology in Changsha, China. In 2016 and in 2017 researchers there conducted studies on detecting people's heads in crowded scenes for the purpose of surveillance. [^localized_region_context] [^replacement_algorithm] diff --git a/site/content/pages/datasets/caltech_10k/index.md b/site/content/pages/datasets/caltech_10k/index.md index b69dbe43..db2383c7 100644 --- a/site/content/pages/datasets/caltech_10k/index.md +++ b/site/content/pages/datasets/caltech_10k/index.md @@ -11,11 +11,11 @@ authors: Adam Harvey ------------ +## Caltech 10K Faces Dataset + ### sidebar ### end sidebar -## Caltech 10K Faces Dataset - [ page under development ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/celeba/index.md b/site/content/pages/datasets/celeba/index.md index 9cdbcad9..3f3aea79 100644 --- a/site/content/pages/datasets/celeba/index.md +++ b/site/content/pages/datasets/celeba/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## CelebA Dataset + ### sidebar ### end sidebar -## CelebA Dataset - [ PAGE UNDER DEVELOPMENT ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/cofw/index.md b/site/content/pages/datasets/cofw/index.md index 4c9f1d61..3cafe5b1 100644 --- a/site/content/pages/datasets/cofw/index.md +++ b/site/content/pages/datasets/cofw/index.md @@ -11,11 +11,11 @@ authors: Adam Harvey ------------ +## Caltech Occluded Faces in the Wild + ### sidebar ### end sidebar -## Caltech Occluded Faces in the Wild - [ PAGE UNDER DEVELOPMENT ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/duke_mtmc/index.md b/site/content/pages/datasets/duke_mtmc/index.md index 37b2cd2d..ac0a3f2e 100644 --- a/site/content/pages/datasets/duke_mtmc/index.md +++ b/site/content/pages/datasets/duke_mtmc/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## Duke MTMC + ### sidebar ### end sidebar -## Duke MTMC - [ page under development ] Duke MTMC (Multi-Target, Multi-Camera Tracking) is a dataset of video recorded on Duke University campus for research and development of networked camera surveillance systems. MTMC tracking algorithms are used for citywide dragnet surveillance systems such as those used throughout China by SenseTime[^sensetime_qz] and the oppressive monitoring of 2.5 million Uyghurs in Xinjiang by SenseNets[^sensenets_uyghurs]. In fact researchers from both SenseTime[^sensetime1] [^sensetime2] and SenseNets[^sensenets_sensetime] used the Duke MTMC dataset for their research. diff --git a/site/content/pages/datasets/feret/index.md b/site/content/pages/datasets/feret/index.md index 15e5ccf0..034ff4aa 100644 --- a/site/content/pages/datasets/feret/index.md +++ b/site/content/pages/datasets/feret/index.md @@ -11,11 +11,11 @@ authors: Adam Harvey ------------ +# FacE REcognition Dataset (FERET) + ### sidebar ### end sidebar -# FacE REcognition Dataset (FERET) - [ page under development ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/hrt_transgender/index.md b/site/content/pages/datasets/hrt_transgender/index.md index 1bca6a33..137e6dcb 100644 --- a/site/content/pages/datasets/hrt_transgender/index.md +++ b/site/content/pages/datasets/hrt_transgender/index.md @@ -14,11 +14,11 @@ authors: Adam Harvey ------------ +## HRT Transgender Dataset + ### sidebar ### end sidebar -## HRT Transgender Dataset - [ page under development ] {% include 'dashboard.html' }
\ No newline at end of file diff --git a/site/content/pages/datasets/lfpw/index.md b/site/content/pages/datasets/lfpw/index.md index 48c0d82a..09506313 100644 --- a/site/content/pages/datasets/lfpw/index.md +++ b/site/content/pages/datasets/lfpw/index.md @@ -11,11 +11,11 @@ authors: Adam Harvey ------------ +## Labeled Face Parts in The Wild + ### sidebar ### end sidebar -## Labeled Face Parts in The Wild - {% include 'dashboard.html' %} -------- diff --git a/site/content/pages/datasets/lfw/index.md b/site/content/pages/datasets/lfw/index.md index bc7f3222..5d90e87f 100644 --- a/site/content/pages/datasets/lfw/index.md +++ b/site/content/pages/datasets/lfw/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## Labeled Faces in the Wild + ### sidebar ### end sidebar -## Labeled Faces in the Wild - [ PAGE UNDER DEVELOPMENT ] *Labeled Faces in The Wild* (LFW) is "a database of face photographs designed for studying the problem of unconstrained face recognition[^lfw_www]. It is used to evaluate and improve the performance of facial recognition algorithms in academic, commercial, and government research. According to BiometricUpdate.com[^lfw_pingan], 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." diff --git a/site/content/pages/datasets/market_1501/index.md b/site/content/pages/datasets/market_1501/index.md index 67558bef..e106a498 100644 --- a/site/content/pages/datasets/market_1501/index.md +++ b/site/content/pages/datasets/market_1501/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## Market-1501 Dataset + ### sidebar ### end sidebar -## Market-1501 Dataset - [ PAGE UNDER DEVELOPMENT] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/msceleb/index.md b/site/content/pages/datasets/msceleb/index.md index 6d45a0aa..70e85699 100644 --- a/site/content/pages/datasets/msceleb/index.md +++ b/site/content/pages/datasets/msceleb/index.md @@ -14,11 +14,11 @@ authors: Adam Harvey ------------ +## Microsoft Celeb Dataset (MS Celeb) + ### sidebar ### end sidebar -## Microsoft Celeb Dataset (MS Celeb) - [ PAGE UNDER DEVELOPMENT ] https://www.hrw.org/news/2019/01/15/letter-microsoft-face-surveillance-technology diff --git a/site/content/pages/datasets/oxford_town_centre/index.md b/site/content/pages/datasets/oxford_town_centre/index.md index c26b81e7..c32cd022 100644 --- a/site/content/pages/datasets/oxford_town_centre/index.md +++ b/site/content/pages/datasets/oxford_town_centre/index.md @@ -14,11 +14,11 @@ authors: Adam Harvey ------------ +## Oxford Town Centre + ### sidebar ### end sidebar -## Oxford Town Centre - The Oxford Town Centre dataset is a CCTV video of pedestrians in a busy downtown area in Oxford used for research and development of activity and face recognition systems.[^ben_benfold_orig] The CCTV video was obtained from a public surveillance camera at the corner of Cornmarket and Market St. in Oxford, England and includes approximately 2,200 people. Since its publication in 2009[^guiding_surveillance] the Oxford Town Centre dataset has been used in over 80 verified research projects including commercial research by Amazon, Disney, OSRAM, and Huawei; and academic research in China, Israel, Russia, Singapore, the US, and Germany among dozens more. The Oxford Town Centre dataset is unique in that it uses footage from a public surveillance camera that would otherwise be designated for public safety. The video shows that the pedestrians act normally and unrehearsed indicating they neither knew of or consented to participation in the research project. diff --git a/site/content/pages/datasets/pipa/index.md b/site/content/pages/datasets/pipa/index.md index fbf535a9..250878ff 100644 --- a/site/content/pages/datasets/pipa/index.md +++ b/site/content/pages/datasets/pipa/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## People in Photo Albums + ### sidebar ### end sidebar -## People in Photo Albums - [ PAGE UNDER DEVELOPMENT ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/pubfig/index.md b/site/content/pages/datasets/pubfig/index.md index 560e66de..5f2e1ad5 100644 --- a/site/content/pages/datasets/pubfig/index.md +++ b/site/content/pages/datasets/pubfig/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## PubFig + ### sidebar ### end sidebar -## PubFig - [ PAGE UNDER DEVELOPMENT ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/uccs/index.md b/site/content/pages/datasets/uccs/index.md index 1ad63f18..68fff4db 100644 --- a/site/content/pages/datasets/uccs/index.md +++ b/site/content/pages/datasets/uccs/index.md @@ -15,15 +15,17 @@ authors: Adam Harvey ------------ +## UnConstrained College Students + ### sidebar ### end sidebar -## UnConstrained College Students - UnConstrained College Students (UCCS) is a dataset of long-range surveillance photos captured at University of Colorado Colorado Springs developed primarily for research and development of "face detection and recognition research towards surveillance applications"[^uccs_vast]. According to the authors of two papers associated with the dataset, over 1,700 students and pedestrians were "photographed using a long-range high-resolution surveillance camera without their knowledge".[^funding_uccs] In this investigation, we examine the contents of the dataset, funding sources, photo EXIF data, and information from publicly available research project citations. + The UCCS dataset includes over 1,700 unique identities, most of which are students walking to and from class. As of 2018, it was the "largest surveillance [face recognition] benchmark in the public domain."[^surv_face_qmul] The photos were taken during the spring semesters of 2012 – 2013 on the West Lawn of the University of Colorado Colorado Springs campus. The photographs were timed to capture students during breaks between their scheduled classes in the morning and afternoon during Monday through Thursday. "For example, a student taking Monday-Wednesday classes at 12:30 PM will show up in the camera on almost every Monday and Wednesday."[^sapkota_boult]. +  The long-range surveillance images in the UnContsrained College Students dataset were captured using a Canon 7D 18 megapixel digital camera fitted with a Sigma 800mm F5.6 EX APO DG HSM telephoto lens and pointed out an office window across the university's West Lawn. The students were photographed from a distance of approximately 150 meters through an office window. "The camera [was] programmed to start capturing images at specific time intervals between classes to maximize the number of faces being captured."[^sapkota_boult] @@ -31,6 +33,8 @@ Their setup made it impossible for students to know they were being photographed  +In the two papers associated with the release of the UCCS dataset ([Unconstrained Face Detection and Open-Set Face Recognition Challenge](https://www.semanticscholar.org/paper/Unconstrained-Face-Detection-and-Open-Set-Face-G%C3%BCnther-Hu/d4f1eb008eb80595bcfdac368e23ae9754e1e745) and [Large Scale Unconstrained Open Set Face Database](https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1)), the researchers disclosed their funding sources as ODNI (United States Office of Director of National Intelligence), IARPA (Intelligence Advance Research Projects Activity), ONR MURI (Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative), Army SBIR (Small Business Innovation Research), SOCOM SBIR (Special Operations Command and Small Business Innovation Research), and the National Science Foundation. Further, UCCS's VAST site explicity [states](https://vast.uccs.edu/project/iarpa-janus/) they are part of the [IARPA Janus](https://www.iarpa.gov/index.php/research-programs/janus), a face recognition project developed to serve the needs of national intelligence interests. + The EXIF data embedded in the images shows that the photo capture times follow a similar pattern, but also highlights that the vast majority of photos (over 7,000) were taken on Tuesdays around noon during students' lunch break. The lack of any photos taken on Friday shows that the researchers were only interested in capturing images of students.  @@ -125,8 +129,6 @@ If you attended University of Colorado Colorado Springs and were captured by the {% include 'cite_our_work.html' %} -{% include 'last_updated.html' %} - ### Footnotes [^uccs_vast]: "2nd Unconstrained Face Detection and Open Set Recognition Challenge." <https://vast.uccs.edu/Opensetface/>. Accessed April 15, 2019. diff --git a/site/content/pages/datasets/vgg_face2/index.md b/site/content/pages/datasets/vgg_face2/index.md index d18d1c2e..acf2476e 100644 --- a/site/content/pages/datasets/vgg_face2/index.md +++ b/site/content/pages/datasets/vgg_face2/index.md @@ -10,12 +10,11 @@ authors: Adam Harvey ------------ +## VGG Face 2 ### sidebar ### end sidebar -## VGG Face 2 - [ page under development ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/viper/index.md b/site/content/pages/datasets/viper/index.md index e6dd167a..291b2136 100644 --- a/site/content/pages/datasets/viper/index.md +++ b/site/content/pages/datasets/viper/index.md @@ -14,11 +14,11 @@ authors: Adam Harvey ------------ +## VIPeR Dataset + ### sidebar ### end sidebar -## VIPeR Dataset - [ page under development ] *VIPeR (Viewpoint Invariant Pedestrian Recognition)* 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." diff --git a/site/content/pages/datasets/youtube_celebrities/index.md b/site/content/pages/datasets/youtube_celebrities/index.md index 6ce2a347..49bfaa2e 100644 --- a/site/content/pages/datasets/youtube_celebrities/index.md +++ b/site/content/pages/datasets/youtube_celebrities/index.md @@ -10,12 +10,11 @@ authors: Adam Harvey ------------ +## YouTube Celebrities ### sidebar ### end sidebar -## YouTube Celebrities - [ page under development ] {% include 'dashboard.html' %} diff --git a/site/public/datasets/50_people_one_question/index.html b/site/public/datasets/50_people_one_question/index.html index dfd8cbff..577d4d8c 100644 --- a/site/public/datasets/50_people_one_question/index.html +++ b/site/public/datasets/50_people_one_question/index.html @@ -27,7 +27,8 @@ <div class="content content-dataset"> <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='right-sidebar'><div class='meta'> +</span></div></div></section><section><h2>50 People 1 Question</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2013</div> </div><div class='meta'> @@ -39,59 +40,8 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='http://www.vision.caltech.edu/~dhall/projects/MergingPoseEstimates/' target='_blank' rel='nofollow noopener'>caltech.edu</a></div> - </div></div><h2>50 People 1 Question</h2> -<p>[ page under development ]</p> -</section><section> - <h3>Who used 50 People One Question 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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how 50 People One Question Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing 50 People One Question 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> + </div><p>[ page under development ]</p> +<p>{% include 'dashboard.html' %}</p> </section> </div> diff --git a/site/public/datasets/afad/index.html b/site/public/datasets/afad/index.html index df14e7cd..6ef13948 100644 --- a/site/public/datasets/afad/index.html +++ b/site/public/datasets/afad/index.html @@ -26,7 +26,8 @@ </header> <div class="content content-"> - <section><div class='right-sidebar'><div class='meta'> + <section><h2>Asian Face Age Dataset</h2> +</section><section><div class='right-sidebar'><div class='meta'> <div class='gray'>Published</div> <div>2017</div> </div><div class='meta'> @@ -41,60 +42,9 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='https://afad-dataset.github.io/' target='_blank' rel='nofollow noopener'>github.io</a></div> - </div></div><h2>Asian Face Age Dataset</h2> -<p>[ page under development ]</p> -</section><section> - <h3>Who used Asian Face Age 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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how Asian Face Age Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing The Asian Face Age Dataset 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><h2>(ignore) research notes</h2> + </div><p>[ page under development ]</p> +<p>{% include 'dashboard.html' %}</p> +</div><h2>(ignore) research notes</h2> <blockquote><p>The Asian Face Age Dataset (AFAD) is a new dataset proposed for evaluating the performance of age estimation, which contains more than 160K facial images and the corresponding age and gender labels. This dataset is oriented to age estimation on Asian faces, so all the facial images are for Asian faces. It is noted that the AFAD is the biggest dataset for age estimation to date. It is well suited to evaluate how deep learning methods can be adopted for age estimation. Motivation</p> <p>For age estimation, there are several public datasets for evaluating the performance of a specific algorithm, such as FG-NET [1] (1002 face images), MORPH I (1690 face images), and MORPH II[2] (55,608 face images). Among them, the MORPH II is the biggest public dataset to date. On the other hand, as we know it is necessary to collect a large scale dataset to train a deep Convolutional Neural Network. Therefore, the MORPH II dataset is extensively used to evaluate how deep learning methods can be adopted for age estimation [3][4].</p> diff --git a/site/public/datasets/brainwash/index.html b/site/public/datasets/brainwash/index.html index 03331a2d..2a6044d0 100644 --- a/site/public/datasets/brainwash/index.html +++ b/site/public/datasets/brainwash/index.html @@ -27,7 +27,8 @@ <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'>Brainwash is a dataset of webcam images taken from the Brainwash Cafe in San Francisco in 2014</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 surveillance algorithms -</span></div></div></section><section><div class='right-sidebar'><div class='meta'> +</span></div></div></section><section><h2>Brainwash Dataset</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2015</div> </div><div class='meta'> @@ -48,71 +49,12 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='https://purl.stanford.edu/sx925dc9385' target='_blank' rel='nofollow noopener'>stanford.edu</a></div> - </div></div><h2>Brainwash Dataset</h2> -<p><em>Brainwash</em> is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 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> captured at 100 second intervals throught the entire day. Brainwash dataset was captured during 3 days in 2014: October 27, November 13, and November 24. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com.<a class="footnote_shim" name="[^end_to_end]_1"> </a><a href="#[^end_to_end]" class="footnote" title="Footnote 2">2</a></p> + </div><p><em>Brainwash</em> is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 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> captured at 100 second intervals throught the entire day. Brainwash dataset was captured during 3 days in 2014: October 27, November 13, and November 24. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com.<a class="footnote_shim" name="[^end_to_end]_1"> </a><a href="#[^end_to_end]" class="footnote" title="Footnote 2">2</a></p> <p>Brainwash is not a widely used dataset but since its publication by Stanford University in 2015, it has notably appeared in several research papers from the National University of Defense Technology in Changsha, China. In 2016 and in 2017 researchers there conducted studies on detecting people's heads in crowded scenes for the purpose of surveillance. <a class="footnote_shim" name="[^localized_region_context]_1"> </a><a href="#[^localized_region_context]" class="footnote" title="Footnote 3">3</a> <a class="footnote_shim" name="[^replacement_algorithm]_1"> </a><a href="#[^replacement_algorithm]" class="footnote" title="Footnote 4">4</a></p> <p>If you happen to have been at Brainwash cafe in San Francisco at any time on October 26, November 13, or November 24 in 2014 you are most likely included in the Brainwash dataset and have unwittingly contributed to surveillance research.</p> -</section><section> - <h3>Who used Brainwash 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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how Brainwash Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Brainwash Dataset 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> - - <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='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/brainwash_saliency_map.jpg' alt=' A visualization of 81,973 head annotations from the Brainwash dataset training partition. © megapixels.cc'><div class='caption'> A visualization of 81,973 head annotations from the Brainwash dataset training partition. © megapixels.cc</div></div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/00425000_960.jpg' alt=' An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)'><div class='caption'> An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)</div></div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/brainwash_montage.jpg' alt=' 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)'><div class='caption'> 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)</div></div></section><section><p>TODO</p> +<p>{% include 'dashboard.html' %}</p> +<p>{% include 'supplementary_header.html' %}</p> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/brainwash_saliency_map.jpg' alt=' A visualization of 81,973 head annotations from the Brainwash dataset training partition. © megapixels.cc'><div class='caption'> A visualization of 81,973 head annotations from the Brainwash dataset training partition. © megapixels.cc</div></div><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/00425000_960.jpg' alt=' An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)'><div class='caption'> An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)</div></div><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/brainwash_montage.jpg' alt=' 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)'><div class='caption'> 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)</div></div><p>TODO</p> <ul> <li>change supp images to 2x2 grid with bboxes</li> <li>add bounding boxes to the header image</li> @@ -120,23 +62,7 @@ <li>add ethics link to Stanford</li> <li>add optout info</li> </ul> -</section><section> - - <h4>Cite Our Work</h4> - <p> - - If you use our data, research, or graphics please cite our work: - -<pre id="cite-bibtex"> -@online{megapixels, - author = {Harvey, Adam. LaPlace, Jules.}, - title = {MegaPixels: Origins, Ethics, and Privacy Implications of Publicly Available Face Recognition Image Datasets}, - year = 2019, - url = {https://megapixels.cc/}, - urldate = {2019-04-20} -}</pre> - - </p> +<p>{% include 'cite_our_work.html' %}</p> </section><section><h3>References</h3><section><ul class="footnotes"><li><a name="[^readme]" class="footnote_shim"></a><span class="backlinks"><a href="#[^readme]_1">a</a></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="[^end_to_end]" class="footnote_shim"></a><span class="backlinks"><a href="#[^end_to_end]_1">a</a></span><p>Stewart, Russel. Andriluka, Mykhaylo. "End-to-end people detection in crowded scenes". 2016.</p> </li><li><a name="[^localized_region_context]" class="footnote_shim"></a><span class="backlinks"><a href="#[^localized_region_context]_1">a</a></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> diff --git a/site/public/datasets/caltech_10k/index.html b/site/public/datasets/caltech_10k/index.html index 00b5e7fd..4cbb7ce6 100644 --- a/site/public/datasets/caltech_10k/index.html +++ b/site/public/datasets/caltech_10k/index.html @@ -26,7 +26,8 @@ </header> <div class="content content-"> - <section><div class='right-sidebar'><div class='meta'> + <section><h2>Caltech 10K Faces Dataset</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2015</div> </div><div class='meta'> @@ -47,60 +48,9 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='https://purl.stanford.edu/sx925dc9385' target='_blank' rel='nofollow noopener'>stanford.edu</a></div> - </div></div><h2>Caltech 10K Faces Dataset</h2> -<p>[ page under development ]</p> -</section><section> - <h3>Who used Brainwash 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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how Brainwash Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Brainwash Dataset 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> + </div><p>[ page under development ]</p> +<p>{% include 'dashboard.html' %}</p> +<h3>(ignore) research notes</h3> <p>The dataset contains images of people collected from the web by typing common given names into Google Image Search. The coordinates of the eyes, the nose and the center of the mouth for each frontal face are provided in a ground truth file. This information can be used to align and crop the human faces or as a ground truth for a face detection algorithm. The dataset has 10,524 human faces of various resolutions and in different settings, e.g. portrait images, groups of people, etc. Profile faces or very low resolution faces are not labeled.</p> </section> diff --git a/site/public/datasets/celeba/index.html b/site/public/datasets/celeba/index.html index c4caef20..9d75b428 100644 --- a/site/public/datasets/celeba/index.html +++ b/site/public/datasets/celeba/index.html @@ -27,7 +27,8 @@ <div class="content content-dataset"> <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='right-sidebar'><div class='meta'> +</span></div></div></section><section><h2>CelebA Dataset</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2015</div> </div><div class='meta'> @@ -45,60 +46,9 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html' target='_blank' rel='nofollow noopener'>edu.hk</a></div> - </div></div><h2>CelebA Dataset</h2> -<p>[ PAGE UNDER DEVELOPMENT ]</p> -</section><section> - <h3>Who used CelebA 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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how CelebA Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Large-scale CelebFaces Attributes Dataset 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>Research</h3> + </div><p>[ PAGE UNDER DEVELOPMENT ]</p> +<p>{% include 'dashboard.html' %}</p> +<h3>Research</h3> <ul> <li>"An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks" mentions use by sponsored by an agency of the United States government. Neither the United States government nor Lawrence Livermore National Security, LLC, nor any of their"</li> <li>7dab6fbf42f82f0f5730fc902f72c3fb628ef2f0</li> diff --git a/site/public/datasets/cofw/index.html b/site/public/datasets/cofw/index.html index 4851e256..084cf7c2 100644 --- a/site/public/datasets/cofw/index.html +++ b/site/public/datasets/cofw/index.html @@ -26,7 +26,8 @@ </header> <div class="content content-"> - <section><div class='right-sidebar'><div class='meta'> + <section><h2>Caltech Occluded Faces in the Wild</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2013</div> </div><div class='meta'> @@ -38,61 +39,10 @@ </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><h2>Caltech Occluded Faces in the Wild</h2> -<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> --> - <div class="applet" data-payload="{"command": "chart"}"></div> -</section> - -<section class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</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> + </div><p>[ PAGE UNDER DEVELOPMENT ]</p> +<p>{% include 'dashboard.html' %}</p> +<h3>(ignore) research notes</h3> +<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><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> @@ -104,58 +54,11 @@ To increase the number of training images, and since COFW has the exact same la <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> +<p>{% include 'map.html' %}</p> +<p>{% include 'supplementary_header.html' %}</p> +<p>{% include 'citations.html' %}</p> +<p>{% include 'chart.html' %}</p> +<p>TODO</p> <h2>- replace graphic</h2> </section> diff --git a/site/public/datasets/duke_mtmc/index.html b/site/public/datasets/duke_mtmc/index.html index c64c0934..3cd19708 100644 --- a/site/public/datasets/duke_mtmc/index.html +++ b/site/public/datasets/duke_mtmc/index.html @@ -27,7 +27,8 @@ <div class="content content-dataset"> <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span class="dataset-name">Duke MTMC</span> is a dataset of surveillance camera footage of students on Duke University campus</span></div><div class='hero_subdesc'><span class='bgpad'>Duke MTMC contains over 2 million video frames and 2,700 unique identities collected from 8 HD cameras at Duke University campus in March 2014 -</span></div></div></section><section><div class='right-sidebar'><div class='meta'> +</span></div></div></section><section><h2>Duke MTMC</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2016</div> </div><div class='meta'> @@ -45,79 +46,21 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='http://vision.cs.duke.edu/DukeMTMC/' target='_blank' rel='nofollow noopener'>duke.edu</a></div> - </div></div><h2>Duke MTMC</h2> -<p>[ page under development ]</p> + </div><p>[ page under development ]</p> <p>Duke MTMC (Multi-Target, Multi-Camera Tracking) is a dataset of video recorded on Duke University campus for research and development of networked camera surveillance systems. MTMC tracking algorithms are used for citywide dragnet surveillance systems such as those used throughout China by SenseTime<a class="footnote_shim" name="[^sensetime_qz]_1"> </a><a href="#[^sensetime_qz]" class="footnote" title="Footnote 1">1</a> and the oppressive monitoring of 2.5 million Uyghurs in Xinjiang by SenseNets<a class="footnote_shim" name="[^sensenets_uyghurs]_1"> </a><a href="#[^sensenets_uyghurs]" class="footnote" title="Footnote 2">2</a>. In fact researchers from both SenseTime<a class="footnote_shim" name="[^sensetime1]_1"> </a><a href="#[^sensetime1]" class="footnote" title="Footnote 4">4</a> <a class="footnote_shim" name="[^sensetime2]_1"> </a><a href="#[^sensetime2]" class="footnote" title="Footnote 5">5</a> and SenseNets<a class="footnote_shim" name="[^sensenets_sensetime]_1"> </a><a href="#[^sensenets_sensetime]" class="footnote" title="Footnote 3">3</a> used the Duke MTMC dataset for their research.</p> <p>In this investigation into the Duke MTMC dataset, we found that researchers at Duke University in Durham, North Carolina captured over 2,000 students, faculty members, and passersby into one of the most prolific public surveillance research datasets that's used around the world by commercial and defense surveillance organizations.</p> <p>Since it's publication in 2016, the Duke MTMC dataset has been used in over 100 studies at organizations around the world including SenseTime<a class="footnote_shim" name="[^sensetime1]_2"> </a><a href="#[^sensetime1]" class="footnote" title="Footnote 4">4</a> <a class="footnote_shim" name="[^sensetime2]_2"> </a><a href="#[^sensetime2]" class="footnote" title="Footnote 5">5</a>, SenseNets<a class="footnote_shim" name="[^sensenets_sensetime]_2"> </a><a href="#[^sensenets_sensetime]" class="footnote" title="Footnote 3">3</a>, IARPA and IBM<a class="footnote_shim" name="[^iarpa_ibm]_1"> </a><a href="#[^iarpa_ibm]" class="footnote" title="Footnote 9">9</a>, Chinese National University of Defense <a class="footnote_shim" name="[^cn_defense1]_1"> </a><a href="#[^cn_defense1]" class="footnote" title="Footnote 7">7</a><a class="footnote_shim" name="[^cn_defense2]_1"> </a><a href="#[^cn_defense2]" class="footnote" title="Footnote 8">8</a>, US Department of Homeland Security<a class="footnote_shim" name="[^us_dhs]_1"> </a><a href="#[^us_dhs]" class="footnote" title="Footnote 10">10</a>, Tencent, Microsoft, Microsft Asia, Fraunhofer, Senstar Corp., Alibaba, Naver Labs, Google and Hewlett-Packard Labs to name only a few.</p> <p>The creation and publication of the Duke MTMC dataset in 2014 (published in 2016) was originally funded by the U.S. Army Research Laboratory and the National Science Foundation<a class="footnote_shim" name="[^duke_mtmc_orig]_1"> </a><a href="#[^duke_mtmc_orig]" class="footnote" title="Footnote 6">6</a>. Though our analysis of the geographic locations of the publicly available research shows over twice as many citations by researchers from China (44% China, 20% United States). In 2018 alone, there were 70 research project citations from China.</p> -</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_reid_montage.jpg' alt=' A collection of 1,600 out of the 2,700 students and passersby captured into the Duke MTMC surveillance research and development dataset on . These students were also included in the Duke MTMC Re-ID dataset extension used for person re-identification. Open Data Commons Attribution License.'><div class='caption'> A collection of 1,600 out of the 2,700 students and passersby captured into the Duke MTMC surveillance research and development dataset on . These students were also included in the Duke MTMC Re-ID dataset extension used for person re-identification. Open Data Commons Attribution License.</div></div></section><section><p>The 8 cameras deployed on Duke's campus were specifically setup to capture students "during periods between lectures, when pedestrian traffic is heavy".<a class="footnote_shim" name="[^duke_mtmc_orig]_2"> </a><a href="#[^duke_mtmc_orig]" class="footnote" title="Footnote 6">6</a>. Camera 5 was positioned to capture students as entering and exiting the university's main chapel. Each camera's location and approximate field of view. The heat map visualization shows the locations where pedestrians were most frequently annotated in each video from the Duke MTMC dataset.</p> -</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_camera_map.jpg' alt=' Duke MTMC camera locations on Duke University campus. Open Data Commons Attribution License.'><div class='caption'> Duke MTMC camera locations on Duke University campus. Open Data Commons Attribution License.</div></div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_cameras.jpg' alt=' Duke MTMC camera views for 8 cameras deployed on campus © megapixels.cc'><div class='caption'> Duke MTMC camera views for 8 cameras deployed on campus © megapixels.cc</div></div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_saliencies.jpg' alt=' Duke MTMC pedestrian detection saliency maps for 8 cameras deployed on campus © megapixels.cc'><div class='caption'> Duke MTMC pedestrian detection saliency maps for 8 cameras deployed on campus © megapixels.cc</div></div></section><section> - <h3>Who used Duke MTMC 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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how Duke MTMC Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Duke Multi-Target, Multi-Camera Tracking Project 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> - - <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><h4>Funding</h4> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_reid_montage.jpg' alt=' A collection of 1,600 out of the 2,700 students and passersby captured into the Duke MTMC surveillance research and development dataset on . These students were also included in the Duke MTMC Re-ID dataset extension used for person re-identification. Open Data Commons Attribution License.'><div class='caption'> A collection of 1,600 out of the 2,700 students and passersby captured into the Duke MTMC surveillance research and development dataset on . These students were also included in the Duke MTMC Re-ID dataset extension used for person re-identification. Open Data Commons Attribution License.</div></div><p>The 8 cameras deployed on Duke's campus were specifically setup to capture students "during periods between lectures, when pedestrian traffic is heavy".<a class="footnote_shim" name="[^duke_mtmc_orig]_2"> </a><a href="#[^duke_mtmc_orig]" class="footnote" title="Footnote 6">6</a>. Camera 5 was positioned to capture students as entering and exiting the university's main chapel. Each camera's location and approximate field of view. The heat map visualization shows the locations where pedestrians were most frequently annotated in each video from the Duke MTMC dataset.</p> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_camera_map.jpg' alt=' Duke MTMC camera locations on Duke University campus. Open Data Commons Attribution License.'><div class='caption'> Duke MTMC camera locations on Duke University campus. Open Data Commons Attribution License.</div></div><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_cameras.jpg' alt=' Duke MTMC camera views for 8 cameras deployed on campus © megapixels.cc'><div class='caption'> Duke MTMC camera views for 8 cameras deployed on campus © megapixels.cc</div></div><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_saliencies.jpg' alt=' Duke MTMC pedestrian detection saliency maps for 8 cameras deployed on campus © megapixels.cc'><div class='caption'> Duke MTMC pedestrian detection saliency maps for 8 cameras deployed on campus © megapixels.cc</div></div><p>{% include 'dashboard.html' %}</p> +<p>{% include 'supplementary_header.html' %}</p> +<h4>Funding</h4> <p>Original funding for the Duke MTMC dataset was provided by the Army Research Office under Grant No. W911NF-10-1-0387 and by the National Science Foundation under Grants IIS-10-17017 and IIS-14-20894.</p> <h4>Video Timestamps</h4> <p>The video timestamps contain the likely, but not yet confirmed, date and times of capture. Because the video timestamps align with the start and stop <a href="http://vision.cs.duke.edu/DukeMTMC/details.html#time-sync">time sync data</a> provided by the researchers, it at least aligns the relative time. The <a href="https://www.wunderground.com/history/daily/KIGX/date/2014-3-19?req_city=Durham&req_state=NC&req_statename=North%20Carolina&reqdb.zip=27708&reqdb.magic=1&reqdb.wmo=99999">rainy weather</a> on that day also contribute towards the likelihood of March 14, 2014..</p> -</section><section><div class='columns columns-2'><div class='column'><table> +<p>=== columns 2</p> +<table> <thead><tr> <th>Camera</th> <th>Date</th> @@ -152,7 +95,8 @@ under Grants IIS-10-17017 and IIS-14-20894.</p> </tr> </tbody> </table> -</div><div class='column'><table> +<p>===========</p> +<table> <thead><tr> <th>Camera</th> <th>Date</th> @@ -187,30 +131,15 @@ under Grants IIS-10-17017 and IIS-14-20894.</p> </tr> </tbody> </table> -</div></div></section><section><h3>Opting Out</h3> +<p>=== end columns</p> +<h3>Opting Out</h3> <p>If you attended Duke University and were captured by any of the 8 surveillance cameras positioned on campus in 2014, there is unfortunately no way to be removed. The dataset files have been distributed throughout the world and it would not be possible to contact all the owners for removal. Nor do the authors provide any options for students to opt-out, nor did they even inform students they would be used at test subjects for surveillance research and development in a project funded, in part, by the United States Army Research Office.</p> <h4>Notes</h4> <ul> <li>The Duke MTMC dataset paper mentions 2,700 identities, but their ground truth file only lists annotations for 1,812</li> </ul> -</section><section> - - <h4>Cite Our Work</h4> - <p> - - If you use our data, research, or graphics please cite our work: - -<pre id="cite-bibtex"> -@online{megapixels, - author = {Harvey, Adam. LaPlace, Jules.}, - title = {MegaPixels: Origins, Ethics, and Privacy Implications of Publicly Available Face Recognition Image Datasets}, - year = 2019, - url = {https://megapixels.cc/}, - urldate = {2019-04-20} -}</pre> - - </p> -</section><section><p>If you use any data from the Duke MTMC please follow their <a href="http://vision.cs.duke.edu/DukeMTMC/#how-to-cite">license</a> and cite their work as:</p> +<p>{% include 'cite_our_work.html' %}</p> +<p>If you use any data from the Duke MTMC please follow their <a href="http://vision.cs.duke.edu/DukeMTMC/#how-to-cite">license</a> and cite their work as:</p> <pre> @inproceedings{ristani2016MTMC, title = {Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking}, diff --git a/site/public/datasets/feret/index.html b/site/public/datasets/feret/index.html index 089cd351..8af139ab 100644 --- a/site/public/datasets/feret/index.html +++ b/site/public/datasets/feret/index.html @@ -26,7 +26,8 @@ </header> <div class="content content-"> - <section><div class='right-sidebar'><div class='meta'> + <section><h1>FacE REcognition Dataset (FERET)</h1> +</section><section><div class='right-sidebar'><div class='meta'> <div class='gray'>Published</div> <div>2007</div> </div><div class='meta'> @@ -41,8 +42,7 @@ </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><h1>FacE REcognition Dataset (FERET)</h1> -<p>[ page under development ]</p> + </div><p>[ page under development ]</p> <p>{% include 'dashboard.html' %}</p> <h3>(ignore) RESEARCH below this line</h3> <ul> diff --git a/site/public/datasets/hrt_transgender/index.html b/site/public/datasets/hrt_transgender/index.html index 231a5271..15cf4807 100644 --- a/site/public/datasets/hrt_transgender/index.html +++ b/site/public/datasets/hrt_transgender/index.html @@ -27,7 +27,8 @@ <div class="content content-dataset"> <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/hrt_transgender/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'>TBD</span></div><div class='hero_subdesc'><span class='bgpad'>TBD -</span></div></div></section><section><div class='right-sidebar'><div class='meta'> +</span></div></div></section><section><h2>HRT Transgender Dataset</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2013</div> </div><div class='meta'> @@ -42,9 +43,8 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='http://www.faceaginggroup.com/hrt-transgender/' target='_blank' rel='nofollow noopener'>faceaginggroup.com</a></div> - </div></div><h2>HRT Transgender Dataset</h2> -<p>[ page under development ]</p> -</section><section><p>{% include 'dashboard.html' }</p> + </div><p>[ page under development ]</p> +<p>{% include 'dashboard.html' }</p> </section> </div> diff --git a/site/public/datasets/lfpw/index.html b/site/public/datasets/lfpw/index.html index f734d332..7f16cd01 100644 --- a/site/public/datasets/lfpw/index.html +++ b/site/public/datasets/lfpw/index.html @@ -26,7 +26,8 @@ </header> <div class="content content-"> - <section><div class='right-sidebar'><div class='meta'> + <section><h2>Labeled Face Parts in The Wild</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2011</div> </div><div class='meta'> @@ -35,59 +36,8 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='http://neerajkumar.org/databases/lfpw/' target='_blank' rel='nofollow noopener'>neerajkumar.org</a></div> - </div></div><h2>Labeled Face Parts in The Wild</h2> -</section><section> - <h3>Who used LFWP?</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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how LFWP has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Labeled Face Parts 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><p>RESEARCH below this line</p> + </div><p>{% include 'dashboard.html' %}</p> +<p>RESEARCH below this line</p> <blockquote><p>Release 1 of LFPW consists of 1,432 faces from images downloaded from the web using simple text queries on sites such as google.com, flickr.com, and yahoo.com. Each image was labeled by three MTurk workers, and 29 fiducial points, shown below, are included in dataset. LFPW was originally described in the following publication:</p> <p>Due to copyright issues, we cannot distribute image files in any format to anyone. Instead, we have made available a list of image URLs where you can download the images yourself. We realize that this makes it impossible to exactly compare numbers, as image links will slowly disappear over time, but we have no other option. This seems to be the way other large web-based databases seem to be evolving.</p> </blockquote> diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html index 2d91b065..54b10611 100644 --- a/site/public/datasets/lfw/index.html +++ b/site/public/datasets/lfw/index.html @@ -27,7 +27,8 @@ <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='right-sidebar'><div class='meta'> +</span></div></div></section><section><h2>Labeled Faces in the Wild</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2007</div> </div><div class='meta'> @@ -42,77 +43,21 @@ </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><h2>Labeled Faces in the Wild</h2> -<p>[ PAGE UNDER DEVELOPMENT ]</p> + </div><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]_1"> </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> <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 class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/lfw_montage_all_crop.jpg' alt='All 5,379 people in the Labeled Faces in The Wild Dataset. Showing one face per person'><div class='caption'>All 5,379 people in the Labeled Faces in The Wild Dataset. Showing one face per person</div></div></section><section><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> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/lfw_montage_all_crop.jpg' alt='All 5,379 people in the Labeled Faces in The Wild Dataset. Showing one face per person'><div class='caption'>All 5,379 people in the Labeled Faces in The Wild Dataset. Showing one face per person</div></div><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> <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>Who used LFW?</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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how LFW has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Labeled 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> - - <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><h3>Commercial Use</h3> +<p>{% include 'dashboard.html' %}</p> +<p>{% include 'supplementary_header.html' %}</p> +<h3>Commercial Use</h3> <p>Add a paragraph about how usage extends far beyond academia into research centers for largest companies in the world. And even funnels into CIA funded research in the US and defense industry usage in China.</p> -</section><section class='applet_container'><div class='applet' data-payload='{"command": "load_file assets/lfw_commercial_use.csv", "fields": ["name_display, company_url, example_url, country, description"]}'></div></section><section><h3>Research</h3> +<pre><code>load_file assets/lfw_commercial_use.csv +name_display, company_url, example_url, country, description +</code></pre> +<h3>Research</h3> <ul> <li>"In our experiments, we used 10000 images and associated captions from the Faces in the wilddata set [3]."</li> <li>"This work was supported in part by the Center for Intelligent Information Retrieval, the Central Intelligence Agency, the National Security Agency and National Science Foundation under CAREER award IIS-0546666 and grant IIS-0326249."</li> @@ -132,7 +77,7 @@ <li>The dataset includes 2 images of <a href="http://vis-www.cs.umass.edu/lfw/person/George_Tenet.html">George Tenet</a>, the former Director of Central Intelligence (DCI) for the Central Intelligence Agency whose facial biometrics were eventually used to help train facial recognition software in China and Russia</li> <li>./15/155205b8e288fd49bf203135871d66de879c8c04/paper.txt shows usage by DSTO Australia, supported parimal@iisc.ac.in</li> </ul> -</section><section><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><section><section><ul> +<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]_2"> </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> diff --git a/site/public/datasets/market_1501/index.html b/site/public/datasets/market_1501/index.html index 72807efc..a76a8859 100644 --- a/site/public/datasets/market_1501/index.html +++ b/site/public/datasets/market_1501/index.html @@ -27,7 +27,8 @@ <div class="content content-dataset"> <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/market_1501/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span class="dataset-name">Market-1501</span> is a dataset is collection of CCTV footage from Tsinghua University</span></div><div class='hero_subdesc'><span class='bgpad'>The Market-1501 dataset includes 1,261 people from 5 HD surveillance cameras located on campus -</span></div></div></section><section><div class='right-sidebar'><div class='meta'> +</span></div></div></section><section><h2>Market-1501 Dataset</h2> +</section><section><div class='right-sidebar'><div class='meta'> <div class='gray'>Published</div> <div>2015</div> </div><div class='meta'> @@ -42,60 +43,9 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='http://www.liangzheng.org/Project/project_reid.html' target='_blank' rel='nofollow noopener'>liangzheng.org</a></div> - </div></div><h2>Market-1501 Dataset</h2> -<p>[ PAGE UNDER DEVELOPMENT]</p> -</section><section> - <h3>Who used Market 1501?</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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how Market 1501 has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Market 1501 Dataset 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><h2>(ignore) research Notes</h2> + </div><p>[ PAGE UNDER DEVELOPMENT]</p> +<p>{% include 'dashboard.html' %}</p> +</div><h2>(ignore) research Notes</h2> <ul> <li>"MARS is an extension of the Market-1501 dataset. During collection, we placed six near synchronized cameras in the campus of Tsinghua university. There were Five 1,080<em>1920 HD cameras and one 640</em>480 SD camera. MARS consists of 1,261 different pedestrians whom are captured by at least 2 cameras. Given a query tracklet, MARS aims to retrieve tracklets that contain the same ID." - main paper</li> <li>bbox "0065C1T0002F0016.jpg", "0065" is the ID of the pedestrian. "C1" denotes the first diff --git a/site/public/datasets/msceleb/index.html b/site/public/datasets/msceleb/index.html index be21280c..60b08b50 100644 --- a/site/public/datasets/msceleb/index.html +++ b/site/public/datasets/msceleb/index.html @@ -27,7 +27,8 @@ <div class="content content-dataset"> <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><div class='right-sidebar'><div class='meta'> +</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'> @@ -48,71 +49,12 @@ </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></div><h2>Microsoft Celeb Dataset (MS Celeb)</h2> -<p>[ PAGE UNDER DEVELOPMENT ]</p> + </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> -</section><section> - <h3>Who used Microsoft Celeb?</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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how Microsoft Celeb has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Microsoft Celebrity Dataset 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> - - <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><h3>Additional Information</h3> +<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> diff --git a/site/public/datasets/oxford_town_centre/index.html b/site/public/datasets/oxford_town_centre/index.html index af020855..d6f7378f 100644 --- a/site/public/datasets/oxford_town_centre/index.html +++ b/site/public/datasets/oxford_town_centre/index.html @@ -27,7 +27,8 @@ <div class="content content-dataset"> <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/oxford_town_centre/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'>Oxford Town Centre is a dataset of surveillance camera footage from Cornmarket St Oxford, England</span></div><div class='hero_subdesc'><span class='bgpad'>The Oxford Town Centre dataset includes approximately 2,200 identities and is used for research and development of face recognition systems -</span></div></div></section><section><div class='right-sidebar'><div class='meta'> +</span></div></div></section><section><h2>Oxford Town Centre</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2009</div> </div><div class='meta'> @@ -48,90 +49,18 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='http://www.robots.ox.ac.uk/ActiveVision/Research/Projects/2009bbenfold_headpose/project.html' target='_blank' rel='nofollow noopener'>ox.ac.uk</a></div> - </div></div><h2>Oxford Town Centre</h2> -<p>The Oxford Town Centre dataset is a CCTV video of pedestrians in a busy downtown area in Oxford used for research and development of activity and face recognition systems.<a class="footnote_shim" name="[^ben_benfold_orig]_1"> </a><a href="#[^ben_benfold_orig]" class="footnote" title="Footnote 1">1</a> The CCTV video was obtained from a public surveillance camera at the corner of Cornmarket and Market St. in Oxford, England and includes approximately 2,200 people. Since its publication in 2009<a class="footnote_shim" name="[^guiding_surveillance]_1"> </a><a href="#[^guiding_surveillance]" class="footnote" title="Footnote 2">2</a> the Oxford Town Centre dataset has been used in over 80 verified research projects including commercial research by Amazon, Disney, OSRAM, and Huawei; and academic research in China, Israel, Russia, Singapore, the US, and Germany among dozens more.</p> + </div><p>The Oxford Town Centre dataset is a CCTV video of pedestrians in a busy downtown area in Oxford used for research and development of activity and face recognition systems.<a class="footnote_shim" name="[^ben_benfold_orig]_1"> </a><a href="#[^ben_benfold_orig]" class="footnote" title="Footnote 1">1</a> The CCTV video was obtained from a public surveillance camera at the corner of Cornmarket and Market St. in Oxford, England and includes approximately 2,200 people. Since its publication in 2009<a class="footnote_shim" name="[^guiding_surveillance]_1"> </a><a href="#[^guiding_surveillance]" class="footnote" title="Footnote 2">2</a> the Oxford Town Centre dataset has been used in over 80 verified research projects including commercial research by Amazon, Disney, OSRAM, and Huawei; and academic research in China, Israel, Russia, Singapore, the US, and Germany among dozens more.</p> <p>The Oxford Town Centre dataset is unique in that it uses footage from a public surveillance camera that would otherwise be designated for public safety. The video shows that the pedestrians act normally and unrehearsed indicating they neither knew of or consented to participation in the research project.</p> -</section><section> - <h3>Who used TownCentre?</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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how TownCentre has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Oxford Town Centre 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> - - <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><h3>Location</h3> +<p>{% include 'dashboard.html' %}</p> +<p>{% include 'supplementary_header.html' %}</p> +<h3>Location</h3> <p>The street location of the camera used for the Oxford Town Centre dataset was confirmed by matching the road, benches, and store signs <a href="https://www.google.com/maps/@51.7528162,-1.2581152,3a,50.3y,310.59h,87.23t/data=!3m7!1e1!3m5!1s3FsGN-PqYC-VhQGjWgmBdQ!2e0!5s20120601T000000!7i13312!8i6656">source</a>. At that location, two public CCTV cameras exist mounted on the side of the Northgate House building at 13-20 Cornmarket St. Because of the lower camera's mounting pole directionality, a view from a private camera in the building across the street can be ruled out because it would have to show more of silhouette of the lower camera's mounting pole. Two options remain: either the public CCTV camera mounted to the side of the building was used or the researchers mounted their own camera to the side of the building in the same location. Because the researchers used many other existing public CCTV cameras for their <a href="http://www.robots.ox.ac.uk/ActiveVision/Research/Projects/2009bbenfold_headpose/project.html">research projects</a> it is likely that they would also be able to access to this camera.</p> <p>To discredit the theory that this public CCTV is only seen pointing the other way in Google Street View images, at least one public photo shows the upper CCTV camera <a href="https://www.oxcivicsoc.org.uk/northgate-house-cornmarket/">pointing in the same direction</a> as the Oxford Town Centre dataset proving the camera can and has been rotated before.</p> <p>As for the capture date, the text on the storefront display shows a sale happening from December 2nd – 7th indicating the capture date was between or just before those dates. The capture year is either 2008 or 2007 since prior to 2007 the Carphone Warehouse (<a href="https://www.flickr.com/photos/katieportwin/364492063/in/photolist-4meWFE-yd7rw-yd7X6-5sDHuc-yd7DN-59CpEK-5GoHAc-yd7Zh-3G2uJP-yd7US-5GomQH-4peYpq-4bAEwm-PALEr-58RkAp-5pHEkf-5v7fGq-4q1J9W-4kypQ2-5KX2Eu-yd7MV-yd7p6-4McgWb-5pJ55w-24N9gj-37u9LK-4FVcKQ-a81Enz-5qNhTG-59CrMZ-2yuwYM-5oagH5-59CdsP-4FVcKN-4PdxhC-5Lhr2j-2PAd2d-5hAwvk-zsQSG-4Cdr4F-3dUPEi-9B1RZ6-2hv5NY-4G5qwP-HCHBW-4JiuC4-4Pdr9Y-584aEV-2GYBEc-HCPkp/">photo</a>, <a href="http://www.oxfordhistory.org.uk/cornmarket/west/47_51.html">history</a>) did not exist at this location. Since the sweaters in the GAP window display are more similar to those in a <a href="web.archive.org/web/20081201002524/http://www.gap.com/">GAP website snapshot</a> from November 2007, our guess is that the footage was obtained during late November or early December 2007. The lack of street vendors and slight waste residue near the bench suggests that is was probably a weekday after rubbish removal.</p> -</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/oxford_town_centre/assets/oxford_town_centre_cctv.jpg' alt=' Footage from this public CCTV camera was used to create the Oxford Town Centre dataset. Image sources: Google Street View (<a href="https://www.google.com/maps/@51.7528162,-1.2581152,3a,50.3y,310.59h,87.23t/data=!3m7!1e1!3m5!1s3FsGN-PqYC-VhQGjWgmBdQ!2e0!5s20120601T000000!7i13312!8i6656">map</a>)'><div class='caption'> Footage from this public CCTV camera was used to create the Oxford Town Centre dataset. Image sources: Google Street View (<a href="https://www.google.com/maps/@51.7528162,-1.2581152,3a,50.3y,310.59h,87.23t/data=!3m7!1e1!3m5!1s3FsGN-PqYC-VhQGjWgmBdQ!2e0!5s20120601T000000!7i13312!8i6656">map</a>)</div></div></section><section><div class='columns columns-'><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/oxford_town_centre/assets/oxford_town_centre_sal_body.jpg' alt=' Heat map body visualization of the pedestrians detected in the Oxford Town Centre dataset © megapixels.cc'><div class='caption'> Heat map body visualization of the pedestrians detected in the Oxford Town Centre dataset © megapixels.cc</div></div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/oxford_town_centre/assets/oxford_town_centre_sal_face.jpg' alt=' Heat map face visualization of the pedestrians detected in the Oxford Town Centre dataset © megapixels.cc'><div class='caption'> Heat map face visualization of the pedestrians detected in the Oxford Town Centre dataset © megapixels.cc</div></div></section></div></section><section> - - <h4>Cite Our Work</h4> - <p> - - If you use our data, research, or graphics please cite our work: - -<pre id="cite-bibtex"> -@online{megapixels, - author = {Harvey, Adam. LaPlace, Jules.}, - title = {MegaPixels: Origins, Ethics, and Privacy Implications of Publicly Available Face Recognition Image Datasets}, - year = 2019, - url = {https://megapixels.cc/}, - urldate = {2019-04-20} -}</pre> - - </p> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/oxford_town_centre/assets/oxford_town_centre_cctv.jpg' alt=' Footage from this public CCTV camera was used to create the Oxford Town Centre dataset. Image sources: Google Street View (<a href="https://www.google.com/maps/@51.7528162,-1.2581152,3a,50.3y,310.59h,87.23t/data=!3m7!1e1!3m5!1s3FsGN-PqYC-VhQGjWgmBdQ!2e0!5s20120601T000000!7i13312!8i6656">map</a>)'><div class='caption'> Footage from this public CCTV camera was used to create the Oxford Town Centre dataset. Image sources: Google Street View (<a href="https://www.google.com/maps/@51.7528162,-1.2581152,3a,50.3y,310.59h,87.23t/data=!3m7!1e1!3m5!1s3FsGN-PqYC-VhQGjWgmBdQ!2e0!5s20120601T000000!7i13312!8i6656">map</a>)</div></div><p>==== columns</p> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/oxford_town_centre/assets/oxford_town_centre_sal_body.jpg' alt=' Heat map body visualization of the pedestrians detected in the Oxford Town Centre dataset © megapixels.cc'><div class='caption'> Heat map body visualization of the pedestrians detected in the Oxford Town Centre dataset © megapixels.cc</div></div><p>====</p> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/oxford_town_centre/assets/oxford_town_centre_sal_face.jpg' alt=' Heat map face visualization of the pedestrians detected in the Oxford Town Centre dataset © megapixels.cc'><div class='caption'> Heat map face visualization of the pedestrians detected in the Oxford Town Centre dataset © megapixels.cc</div></div><p>=== end columns</p> +<p>{% include 'cite_our_work.html' %}</p> </section><section><h3>References</h3><section><ul class="footnotes"><li><a name="[^ben_benfold_orig]" class="footnote_shim"></a><span class="backlinks"><a href="#[^ben_benfold_orig]_1">a</a></span><p>Benfold, Ben and Reid, Ian. "Stable Multi-Target Tracking in Real-Time Surveillance Video". CVPR 2011. Pages 3457-3464.</p> </li><li><a name="[^guiding_surveillance]" class="footnote_shim"></a><span class="backlinks"><a href="#[^guiding_surveillance]_1">a</a></span><p>"Guiding Visual Surveillance by Tracking Human Attention". 2009.</p> </li></ul></section></section> diff --git a/site/public/datasets/pipa/index.html b/site/public/datasets/pipa/index.html index 780b3029..28da8d4b 100644 --- a/site/public/datasets/pipa/index.html +++ b/site/public/datasets/pipa/index.html @@ -27,7 +27,8 @@ <div class="content content-dataset"> <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/pipa/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span class="dataset-name"> People in Photo Albums (PIPA)</span> is a dataset...</span></div><div class='hero_subdesc'><span class='bgpad'>[ add subdescrition ] -</span></div></div></section><section><div class='right-sidebar'><div class='meta'> +</span></div></div></section><section><h2>People in Photo Albums</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2015</div> </div><div class='meta'> @@ -45,59 +46,8 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='https://people.eecs.berkeley.edu/~nzhang/piper.html' target='_blank' rel='nofollow noopener'>berkeley.edu</a></div> - </div></div><h2>People in Photo Albums</h2> -<p>[ PAGE UNDER DEVELOPMENT ]</p> -</section><section> - <h3>Who used PIPA 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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how PIPA Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing People in Photo Albums Dataset 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> + </div><p>[ PAGE UNDER DEVELOPMENT ]</p> +<p>{% include 'dashboard.html' %}</p> </section> </div> diff --git a/site/public/datasets/pubfig/index.html b/site/public/datasets/pubfig/index.html index 2c8bd7b1..1a6ffebf 100644 --- a/site/public/datasets/pubfig/index.html +++ b/site/public/datasets/pubfig/index.html @@ -27,7 +27,8 @@ <div class="content content-dataset"> <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/pubfig/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span class="dataset-name">PubFig</span> is a dataset...</span></div><div class='hero_subdesc'><span class='bgpad'>[ add subdescrition ] -</span></div></div></section><section><div class='right-sidebar'><div class='meta'> +</span></div></div></section><section><h2>PubFig</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2009</div> </div><div class='meta'> @@ -42,59 +43,8 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='http://www.cs.columbia.edu/CAVE/databases/pubfig/' target='_blank' rel='nofollow noopener'>columbia.edu</a></div> - </div></div><h2>PubFig</h2> -<p>[ PAGE UNDER DEVELOPMENT ]</p> -</section><section> - <h3>Who used PubFig?</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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how PubFig has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Public Figures Face Dataset 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> + </div><p>[ PAGE UNDER DEVELOPMENT ]</p> +<p>{% include 'dashboard.html' %}</p> </section> </div> diff --git a/site/public/datasets/uccs/index.html b/site/public/datasets/uccs/index.html index 42774635..4c106922 100644 --- a/site/public/datasets/uccs/index.html +++ b/site/public/datasets/uccs/index.html @@ -27,7 +27,8 @@ <div class="content content-dataset"> <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span class="dataset-name">UnConstrained College Students</span> is a dataset of long-range surveillance photos of students on University of Colorado in Colorado Springs campus</span></div><div class='hero_subdesc'><span class='bgpad'>The UnConstrained College Students dataset includes 16,149 images of 1,732 students, faculty, and pedestrians and is used for developing face recognition and face detection algorithms -</span></div></div></section><section><div class='right-sidebar'><div class='meta'> +</span></div></div></section><section><h2>UnConstrained College Students</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2016</div> </div><div class='meta'> @@ -48,77 +49,20 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='http://vast.uccs.edu/Opensetface/' target='_blank' rel='nofollow noopener'>uccs.edu</a></div> - </div></div><h2>UnConstrained College Students</h2> -<p>UnConstrained College Students (UCCS) is a dataset of long-range surveillance photos captured at University of Colorado Colorado Springs developed primarily for research and development of "face detection and recognition research towards surveillance applications"<a class="footnote_shim" name="[^uccs_vast]_1"> </a><a href="#[^uccs_vast]" class="footnote" title="Footnote 1">1</a>. According to the authors of two papers associated with the dataset, over 1,700 students and pedestrians were "photographed using a long-range high-resolution surveillance camera without their knowledge".<a class="footnote_shim" name="[^funding_uccs]_1"> </a><a href="#[^funding_uccs]" class="footnote" title="Footnote 3">3</a> In this investigation, we examine the contents of the dataset, funding sources, photo EXIF data, and information from publicly available research project citations.</p> + </div><p>UnConstrained College Students (UCCS) is a dataset of long-range surveillance photos captured at University of Colorado Colorado Springs developed primarily for research and development of "face detection and recognition research towards surveillance applications"<a class="footnote_shim" name="[^uccs_vast]_1"> </a><a href="#[^uccs_vast]" class="footnote" title="Footnote 1">1</a>. According to the authors of two papers associated with the dataset, over 1,700 students and pedestrians were "photographed using a long-range high-resolution surveillance camera without their knowledge".<a class="footnote_shim" name="[^funding_uccs]_1"> </a><a href="#[^funding_uccs]" class="footnote" title="Footnote 3">3</a> In this investigation, we examine the contents of the dataset, funding sources, photo EXIF data, and information from publicly available research project citations.</p> <p>The UCCS dataset includes over 1,700 unique identities, most of which are students walking to and from class. As of 2018, it was the "largest surveillance [face recognition] benchmark in the public domain."<a class="footnote_shim" name="[^surv_face_qmul]_1"> </a><a href="#[^surv_face_qmul]" class="footnote" title="Footnote 4">4</a> The photos were taken during the spring semesters of 2012 – 2013 on the West Lawn of the University of Colorado Colorado Springs campus. The photographs were timed to capture students during breaks between their scheduled classes in the morning and afternoon during Monday through Thursday. "For example, a student taking Monday-Wednesday classes at 12:30 PM will show up in the camera on almost every Monday and Wednesday."<a class="footnote_shim" name="[^sapkota_boult]_1"> </a><a href="#[^sapkota_boult]" class="footnote" title="Footnote 2">2</a>.</p> -</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_grid.jpg' alt=' Example images from the UnConstrained College Students Dataset. '><div class='caption'> Example images from the UnConstrained College Students Dataset. </div></div></section><section><p>The long-range surveillance images in the UnContsrained College Students dataset were captured using a Canon 7D 18 megapixel digital camera fitted with a Sigma 800mm F5.6 EX APO DG HSM telephoto lens and pointed out an office window across the university's West Lawn. The students were photographed from a distance of approximately 150 meters through an office window. "The camera [was] programmed to start capturing images at specific time intervals between classes to maximize the number of faces being captured."<a class="footnote_shim" name="[^sapkota_boult]_2"> </a><a href="#[^sapkota_boult]" class="footnote" title="Footnote 2">2</a> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_grid.jpg' alt=' Example images from the UnConstrained College Students Dataset. '><div class='caption'> Example images from the UnConstrained College Students Dataset. </div></div><p>The long-range surveillance images in the UnContsrained College Students dataset were captured using a Canon 7D 18 megapixel digital camera fitted with a Sigma 800mm F5.6 EX APO DG HSM telephoto lens and pointed out an office window across the university's West Lawn. The students were photographed from a distance of approximately 150 meters through an office window. "The camera [was] programmed to start capturing images at specific time intervals between classes to maximize the number of faces being captured."<a class="footnote_shim" name="[^sapkota_boult]_2"> </a><a href="#[^sapkota_boult]" class="footnote" title="Footnote 2">2</a> Their setup made it impossible for students to know they were being photographed, providing the researchers with realistic surveillance images to help build face detection and recognition systems for real world applications in defense, intelligence, and commercial applications.</p> -</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_map_aerial.jpg' alt=' The location at University of Colorado Colorado Springs where students were surreptitiously photographed with a long-range surveillance camera for use in a defense and intelligence agency funded research project on face recognition. Image: Google Maps'><div class='caption'> The location at University of Colorado Colorado Springs where students were surreptitiously photographed with a long-range surveillance camera for use in a defense and intelligence agency funded research project on face recognition. Image: Google Maps</div></div></section><section><p>The EXIF data embedded in the images shows that the photo capture times follow a similar pattern, but also highlights that the vast majority of photos (over 7,000) were taken on Tuesdays around noon during students' lunch break. The lack of any photos taken on Friday shows that the researchers were only interested in capturing images of students.</p> -</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_exif_plot_days.png' alt=' UCCS photos captured per weekday © megapixels.cc'><div class='caption'> UCCS photos captured per weekday © megapixels.cc</div></div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_exif_plot.png' alt=' UCCS photos captured per weekday © megapixels.cc'><div class='caption'> UCCS photos captured per weekday © megapixels.cc</div></div></section><section><p>The two research papers associated with the release of the UCCS dataset (<a href="https://www.semanticscholar.org/paper/Unconstrained-Face-Detection-and-Open-Set-Face-G%C3%BCnther-Hu/d4f1eb008eb80595bcfdac368e23ae9754e1e745">Unconstrained Face Detection and Open-Set Face Recognition Challenge</a> and <a href="https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1">Large Scale Unconstrained Open Set Face Database</a>), acknowledge that the primary funding sources for their work were United States defense and intelligence agencies. Specifically, development of the UnContrianed College Students dataset was funded by the Intelligence Advanced Research Projects Activity (IARPA), Office of Director of National Intelligence (ODNI), Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative (ONR MURI), Small Business Innovation Research (SBIR), Special Operations Command and Small Business Innovation Research (SOCOM SBIR), and the National Science Foundation. Further, UCCS's VAST site explicitly <a href="https://vast.uccs.edu/project/iarpa-janus/">states</a> they are part of the <a href="https://www.iarpa.gov/index.php/research-programs/janus">IARPA Janus</a>, a face recognition project developed to serve the needs of national intelligence interests, clearly establishing the the funding sources and immediate benefactors of this dataset are United States defense and intelligence agencies.</p> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_map_aerial.jpg' alt=' The location at University of Colorado Colorado Springs where students were surreptitiously photographed with a long-range surveillance camera for use in a defense and intelligence agency funded research project on face recognition. Image: Google Maps'><div class='caption'> The location at University of Colorado Colorado Springs where students were surreptitiously photographed with a long-range surveillance camera for use in a defense and intelligence agency funded research project on face recognition. Image: Google Maps</div></div><p>In the two papers associated with the release of the UCCS dataset (<a href="https://www.semanticscholar.org/paper/Unconstrained-Face-Detection-and-Open-Set-Face-G%C3%BCnther-Hu/d4f1eb008eb80595bcfdac368e23ae9754e1e745">Unconstrained Face Detection and Open-Set Face Recognition Challenge</a> and <a href="https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1">Large Scale Unconstrained Open Set Face Database</a>), the researchers disclosed their funding sources as ODNI (United States Office of Director of National Intelligence), IARPA (Intelligence Advance Research Projects Activity), ONR MURI (Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative), Army SBIR (Small Business Innovation Research), SOCOM SBIR (Special Operations Command and Small Business Innovation Research), and the National Science Foundation. Further, UCCS's VAST site explicity <a href="https://vast.uccs.edu/project/iarpa-janus/">states</a> they are part of the <a href="https://www.iarpa.gov/index.php/research-programs/janus">IARPA Janus</a>, a face recognition project developed to serve the needs of national intelligence interests.</p> +<p>The EXIF data embedded in the images shows that the photo capture times follow a similar pattern, but also highlights that the vast majority of photos (over 7,000) were taken on Tuesdays around noon during students' lunch break. The lack of any photos taken on Friday shows that the researchers were only interested in capturing images of students.</p> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_exif_plot_days.png' alt=' UCCS photos captured per weekday © megapixels.cc'><div class='caption'> UCCS photos captured per weekday © megapixels.cc</div></div><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_exif_plot.png' alt=' UCCS photos captured per weekday © megapixels.cc'><div class='caption'> UCCS photos captured per weekday © megapixels.cc</div></div><p>The two research papers associated with the release of the UCCS dataset (<a href="https://www.semanticscholar.org/paper/Unconstrained-Face-Detection-and-Open-Set-Face-G%C3%BCnther-Hu/d4f1eb008eb80595bcfdac368e23ae9754e1e745">Unconstrained Face Detection and Open-Set Face Recognition Challenge</a> and <a href="https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1">Large Scale Unconstrained Open Set Face Database</a>), acknowledge that the primary funding sources for their work were United States defense and intelligence agencies. Specifically, development of the UnContrianed College Students dataset was funded by the Intelligence Advanced Research Projects Activity (IARPA), Office of Director of National Intelligence (ODNI), Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative (ONR MURI), Small Business Innovation Research (SBIR), Special Operations Command and Small Business Innovation Research (SOCOM SBIR), and the National Science Foundation. Further, UCCS's VAST site explicitly <a href="https://vast.uccs.edu/project/iarpa-janus/">states</a> they are part of the <a href="https://www.iarpa.gov/index.php/research-programs/janus">IARPA Janus</a>, a face recognition project developed to serve the needs of national intelligence interests, clearly establishing the the funding sources and immediate benefactors of this dataset are United States defense and intelligence agencies.</p> <p>Although the images were first captured in 2012 – 2013 the dataset was not publicly released until 2016. Then in 2017 the UCCS face dataset formed the basis for a defense and intelligence agency funded <a href="http://www.face-recognition-challenge.com/">face recognition challenge</a> project at the International Joint Biometrics Conference in Denver, CO. And in 2018 the dataset was again used for the <a href="https://erodner.github.io/ial2018eccv/">2nd Unconstrained Face Detection and Open Set Recognition Challenge</a> at the European Computer Vision Conference (ECCV) in Munich, Germany.</p> <p>As of April 15, 2019, the UCCS dataset is no longer available for public download. But during the three years it was publicly available (2016-2019) the UCCS dataset appeared in at least 6 publicly available research papers including verified usage from Beihang University who is known to provide research and development for China's military.</p> -</section><section> - <h3>Who used UCCS?</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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how UCCS has been used around the world by commercial, military, and academic organizations; existing publicly available research citing UnConstrained College Students Dataset 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> - - <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><p>To show the types of face images used in the UCCS student dataset while protecting their individual privacy, a generative adversarial network was used to interpolate between identities in the dataset. The image below shows a generative adversarial network trained on the UCCS face bounding box areas from 16,000 images and over 90,000 face regions.</p> -</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_pgan_01.jpg' alt=' GAN generated approximations of students in the UCCS dataset. © megapixels.cc 2018'><div class='caption'> GAN generated approximations of students in the UCCS dataset. © megapixels.cc 2018</div></div></section><section><div class='columns columns-2'><div class='column'><h4>UCCS photos taken in 2012</h4> +<p>{% include 'dashboard.html' %}</p> +<p>{% include 'supplementary_header.html' %}</p> +<p>To show the types of face images used in the UCCS student dataset while protecting their individual privacy, a generative adversarial network was used to interpolate between identities in the dataset. The image below shows a generative adversarial network trained on the UCCS face bounding box areas from 16,000 images and over 90,000 face regions.</p> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_pgan_01.jpg' alt=' GAN generated approximations of students in the UCCS dataset. © megapixels.cc 2018'><div class='caption'> GAN generated approximations of students in the UCCS dataset. © megapixels.cc 2018</div></div><p>=== columns 2</p> +<h4>UCCS photos taken in 2012</h4> <table> <thead><tr> <th>Date</th> @@ -176,7 +120,8 @@ Their setup made it impossible for students to know they were being photographed </tr> </tbody> </table> -</div><div class='column'><h4>UCCS photos taken in 2013</h4> +<p>===========</p> +<h4>UCCS photos taken in 2013</h4> <table> <thead><tr> <th>Date</th> @@ -210,9 +155,10 @@ Their setup made it impossible for students to know they were being photographed </tr> </tbody> </table> -</div></div></section><section><h3>Location</h3> +<p>=== end columns</p> +<h3>Location</h3> <p>The location of the camera and subjects can confirmed using several visual cues in the dataset images: the unique pattern of the sidewalk that is only used on the UCCS Pedestrian Spine near the West Lawn, the two UCCS sign poles with matching graphics still visible in Google Street View, the no parking sign and directionality of its arrow, the back of street sign next to it, the slight bend in the sidewalk, the presence of cars passing in the background of the image, and the far wall of the parking garage all match images in the dataset. The <a href="https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1">original papers</a> also provides another clue: a <a href="https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1/figure/1">picture of the camera</a> inside the office that was used to create the dataset. The window view in this image provides another match for the brick pattern on the north facade of the Kraember Family Library and the green metal fence along the sidewalk. View the <a href="https://www.google.com/maps/place/University+of+Colorado+Colorado+Springs/@38.8934297,-104.7992445,27a,35y,258.51h,75.06t/data=!3m1!1e3!4m5!3m4!1s0x87134fa088fe399d:0x92cadf3962c058c4!8m2!3d38.8968312!4d-104.8049528">location on Google Maps</a></p> -</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_map_3d.jpg' alt=' 3D view showing the angle of view of the surveillance camera used for UCCS dataset. Image: Google Maps'><div class='caption'> 3D view showing the angle of view of the surveillance camera used for UCCS dataset. Image: Google Maps</div></div></section><section><h3>Funding</h3> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_map_3d.jpg' alt=' 3D view showing the angle of view of the surveillance camera used for UCCS dataset. Image: Google Maps'><div class='caption'> 3D view showing the angle of view of the surveillance camera used for UCCS dataset. Image: Google Maps</div></div><h3>Funding</h3> <p>The UnConstrained College Students dataset is associated with two main research papers: "Large Scale Unconstrained Open Set Face Database" and "Unconstrained Face Detection and Open-Set Face Recognition Challenge". Collectively, these papers and the creation of the dataset have received funding from the following organizations:</p> <ul> <li>ONR (Office of Naval Research) MURI (The Department of Defense Multidisciplinary University Research Initiative) grant N00014-08-1-0638</li> @@ -233,25 +179,7 @@ Their setup made it impossible for students to know they were being photographed <ul> <li>Download EXIF data for UCCS photos: <a href="https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_camera_exif.csv">uccs_camera_exif.csv</a></li> </ul> -</section><section> - - <h4>Cite Our Work</h4> - <p> - - If you use our data, research, or graphics please cite our work: - -<pre id="cite-bibtex"> -@online{megapixels, - author = {Harvey, Adam. LaPlace, Jules.}, - title = {MegaPixels: Origins, Ethics, and Privacy Implications of Publicly Available Face Recognition Image Datasets}, - year = 2019, - url = {https://megapixels.cc/}, - urldate = {2019-04-20} -}</pre> - - </p> -</section><section> - <p>This page was last updated on 2019-4-15</p> +<p>{% include 'cite_our_work.html' %}</p> </section><section><h3>References</h3><section><ul class="footnotes"><li><a name="[^uccs_vast]" class="footnote_shim"></a><span class="backlinks"><a href="#[^uccs_vast]_1">a</a></span><p>"2nd Unconstrained Face Detection and Open Set Recognition Challenge." <a href="https://vast.uccs.edu/Opensetface/">https://vast.uccs.edu/Opensetface/</a>. Accessed April 15, 2019.</p> </li><li><a name="[^sapkota_boult]" class="footnote_shim"></a><span class="backlinks"><a href="#[^sapkota_boult]_1">a</a><a href="#[^sapkota_boult]_2">b</a></span><p>Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013.</p> </li><li><a name="[^funding_uccs]" class="footnote_shim"></a><span class="backlinks"><a href="#[^funding_uccs]_1">a</a></span><p>Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3.</p> diff --git a/site/public/datasets/vgg_face2/index.html b/site/public/datasets/vgg_face2/index.html index 75d73824..e23a3afd 100644 --- a/site/public/datasets/vgg_face2/index.html +++ b/site/public/datasets/vgg_face2/index.html @@ -26,7 +26,8 @@ </header> <div class="content content-"> - <section><div class='right-sidebar'><div class='meta'> + <section><h2>VGG Face 2</h2> +</section><section><div class='right-sidebar'><div class='meta'> <div class='gray'>Published</div> <div>2015</div> </div><div class='meta'> @@ -47,60 +48,9 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='https://purl.stanford.edu/sx925dc9385' target='_blank' rel='nofollow noopener'>stanford.edu</a></div> - </div></div><h2>VGG Face 2</h2> -<p>[ page under development ]</p> -</section><section> - <h3>Who used Brainwash 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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how Brainwash Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Brainwash Dataset 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> + </div><p>[ page under development ]</p> +<p>{% include 'dashboard.html' %}</p> +<h3>(ignore) research notes</h3> <ul> <li>The VGG Face 2 dataset includes approximately 1,331 actresses, 139 presidents, 16 wives, 3 husbands, 2 snooker player, and 1 guru</li> <li>The original VGGF2 name list has been updated with the results returned from Google Knowledge</li> @@ -108,7 +58,7 @@ <li>The 97 names with a score of 0.75 or lower were manually reviewed and includes name changes validating using Wikipedia.org results for names such as "Bruce Jenner" to "Caitlyn Jenner", spousal last-name changes, and discretionary changes to improve search results such as combining nicknames with full name when appropriate, for example changing "Aleksandar Petrović" to "Aleksandar 'Aco' Petrović" and minor changes such as "Mohammad Ali" to "Muhammad Ali"</li> <li>The 'Description' text was automatically added when the Knowledge Graph score was greater than 250</li> </ul> -<h2>TODO</h2> +</div><h2>TODO</h2> <ul> <li>create name list, and populate with Knowledge graph information like LFW</li> <li>make list of interesting number stats, by the numbers</li> diff --git a/site/public/datasets/viper/index.html b/site/public/datasets/viper/index.html index 5b3ac35b..6f646bb8 100644 --- a/site/public/datasets/viper/index.html +++ b/site/public/datasets/viper/index.html @@ -27,7 +27,8 @@ <div class="content content-dataset"> <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 class="dataset-name">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='right-sidebar'><div class='meta'> +</span></div></div></section><section><h2>VIPeR Dataset</h2> +</section><section><div class='meta'> <div class='gray'>Published</div> <div>2007</div> </div><div class='meta'> @@ -45,61 +46,10 @@ </div><div class='meta'> <div class='gray'>Website</div> <div><a href='https://vision.soe.ucsc.edu/node/178' target='_blank' rel='nofollow noopener'>ucsc.edu</a></div> - </div></div><h2>VIPeR Dataset</h2> -<p>[ page under development ]</p> + </div><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 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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how VIPeR has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Viewpoint Invariant Pedestrian Recognition 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> +<p>{% include 'dashboard.html' %}</p> </section> </div> diff --git a/site/public/datasets/youtube_celebrities/index.html b/site/public/datasets/youtube_celebrities/index.html index 39670c19..c491e6af 100644 --- a/site/public/datasets/youtube_celebrities/index.html +++ b/site/public/datasets/youtube_celebrities/index.html @@ -26,60 +26,10 @@ </header> <div class="content content-"> - <section><div class='right-sidebar'></div><h2>YouTube Celebrities</h2> -<p>[ page under development ]</p> -</section><section> - <h3>Who used YouTube Celebrities?</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 class="applet_container"> - <div class="applet" data-payload="{"command": "piechart"}"></div> -</section> - -<section> - - <h3>Biometric Trade Routes</h3> - - <p> - To help understand how YouTube Celebrities has been used around the world by commercial, military, and academic organizations; existing publicly available research citing YouTube Celebrities 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><h4>Notes...</h4> + <section><h2>YouTube Celebrities</h2> +</section><section><p>[ page under development ]</p> +<p>{% include 'dashboard.html' %}</p> +<h4>Notes...</h4> <ul> <li>Selected dataset sequences: (a) MBGC, (b) CMU MoBo, (c) First Honda/UCSD, and (d) YouTube Celebrities.</li> |