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33 files changed, 292 insertions, 87 deletions
diff --git a/site/assets/css/css.css b/site/assets/css/css.css index 47106dd9..69302409 100644 --- a/site/assets/css/css.css +++ b/site/assets/css/css.css @@ -481,6 +481,46 @@ section.fullwidth .image { color:#fff; border: 0; } + + +/* about page */ + +.flex-container { + padding: 0; + margin: 0; + list-style: none; + + display: -webkit-box; + display: -moz-box; + display: -ms-flexbox; + display: -webkit-flex; + display: flex; + + -webkit-flex-flow: row wrap; + justify-content: space-around; +} + +.team-member { + height: auto; + margin-top: 10px; + color: white; + width: 400px; + font-weight: bold; + flex-grow: 1; + margin:0 40px 0 0; +} +.team-member&:last-child{ + margin:0 0 0 40px; +} +.team-member p{ + font-size:14px; +} +.team-member img{ + margin:0; + display: block; +} + + .sideimage { margin: 0px 0 40px 0; display: flex; @@ -491,6 +531,7 @@ section.fullwidth .image { .sideimage p{ margin-top:0px; padding-top:0px; + font-size:14px; } .sideimage strong{ display: block; diff --git a/site/content/pages/about/assets/adam-harvey-3d.jpg b/site/content/pages/about/assets/adam-harvey-3d.jpg Binary files differnew file mode 100644 index 00000000..2d7cbd80 --- /dev/null +++ b/site/content/pages/about/assets/adam-harvey-3d.jpg diff --git a/site/content/pages/about/assets/adam-harvey-3d.png b/site/content/pages/about/assets/adam-harvey-3d.png Binary files differnew file mode 100644 index 00000000..3616e851 --- /dev/null +++ b/site/content/pages/about/assets/adam-harvey-3d.png diff --git a/site/content/pages/about/assets/adam-harvey.jpg b/site/content/pages/about/assets/adam-harvey.jpg Binary files differindex e0ab893a..38a484d1 100644 --- a/site/content/pages/about/assets/adam-harvey.jpg +++ b/site/content/pages/about/assets/adam-harvey.jpg diff --git a/site/content/pages/about/assets/jules-laplace-3d.jpg b/site/content/pages/about/assets/jules-laplace-3d.jpg Binary files differnew file mode 100644 index 00000000..d51e0933 --- /dev/null +++ b/site/content/pages/about/assets/jules-laplace-3d.jpg diff --git a/site/content/pages/about/assets/jules-laplace.jpg b/site/content/pages/about/assets/jules-laplace.jpg Binary files differindex 310b2783..18fc1170 100644 --- a/site/content/pages/about/assets/jules-laplace.jpg +++ b/site/content/pages/about/assets/jules-laplace.jpg diff --git a/site/content/pages/about/credits.md b/site/content/pages/about/credits.md new file mode 100644 index 00000000..3ad962df --- /dev/null +++ b/site/content/pages/about/credits.md @@ -0,0 +1,43 @@ +------------ + +status: published +title: MegaPixels Press and News +desc: MegaPixels Press and News +slug: press +cssclass: about +published: 2018-12-04 +updated: 2018-12-04 +authors: Adam Harvey + +------------ + +# Credits + +<section class="about-menu"> +<ul> + <li><a href="/about/">About</a></li> + <li><a href="/about/press/">Press</a></li> + <li><a class="current" href="/about/credits/">Credits</a></li> + <li><a href="/about/disclaimer/">Disclaimer</a></li> + <li><a href="/about/terms/">Terms and Conditions</a></li> + <li><a href="/about/privacy/">Privacy Policy</a></li> +</ul> +</section> + + +#### Team + +- Research, concept: Adam Harvey +- Site development, visualizations: Jules LaPlace +- Assistant researcher: Berit Gilma +- Produced in Partnership with Mozilla + +#### Code + +- This site uses D3 and C2 for visuzations. +- Add more here + +#### Data + +- link to github +- how it was gathered
\ No newline at end of file diff --git a/site/content/pages/about/disclaimer.md b/site/content/pages/about/disclaimer.md index 97edc461..f82a09a0 100644 --- a/site/content/pages/about/disclaimer.md +++ b/site/content/pages/about/disclaimer.md @@ -17,15 +17,14 @@ authors: Adam Harvey <ul> <li><a href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> +<li><a href="/about/credits/">Credits</a></li> <li><a class="current" href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> </section> -### Sidebar - -## End Sidebar +(TEMPORARY PAGE) Last updated: December 04, 2018 diff --git a/site/content/pages/about/index.md b/site/content/pages/about/index.md index dbf4e1bb..b1b7a80f 100644 --- a/site/content/pages/about/index.md +++ b/site/content/pages/about/index.md @@ -17,23 +17,34 @@ authors: Adam Harvey <ul> <li><a class="current" href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> +<li><a href="/about/credits/">Credits</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> </section> -<p><div style="font-size:20px;line-height:36px">Ever since government agencies began developing face recognition in the early 1960's, datasets of face images have always been central to the development and evaluation of their algorithms. Today, these datasets no longer originate in labs, but instead from family photos albums posted on Flickr, CCTV cameras on college campuses, livestreams at cafes, search engine queries for celebrities, or <a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">videos on YouTube</a>. </div></p> +(PAGE UNDER DEVELOPMENT) -While these datasets include many public figures, politicans, athletes, and actors, they also include many non-public figures including digital activists, students, and pedestrians. Some images are used with creative commons licenses, but others were taken in unconstrained scenarios without anyone's awareness or consent. During the last year hundreds of these datasets have been collected to understand how they contribute to a global supply chain of biometric data. +<p><div style="font-size:20px;line-height:36px">MegaPixels is art and research by <a href="https://ahprojects.com">Adam Harvey</a> about facial recognition datasets that aims to unravel their histories, futures, geographies, and meanings. Throughout 2019 this site, coded by Jules LaPlace, will publish research reports, visualizations, raw data, and interactive tools to explore how publicly available facial recognition datasets contribute to a global supply chain of biometric data that powers the global facial recognition industry.</div></p> -MegaPixels is art and research by <a href="https://ahprojects.com">Adam Harvey</a> about publicly available facial recognition datasets that aims to unravel the stories behind these datasets. During 2019 this site, coded by Jules LaPlace, will publish research reports, visualizations, downloadable statisticds, and interactive tools for searching the datasets. +The MegaPixels website is produced in partnership with [Mozilla](https://mozilla.org). -This project is produced in partnership with [Mozilla](https://mozilla.org) who has provided the funding to research the datasets, build the site, and develop tools to help you understand the role these datasets have played in creating biometric surveillance technologies. - - -## Team - - **Adam Harvey** is Berlin-based American artist and researcher. His previous projects (CV Dazzle, Stealth Wear, and SkyLift) explore the potential for countersurveillance as artwork. He is the founder of VFRAME (visual forensics software for human rights groups), the recipient of 2 PrototypeFund awards, and a researcher in residence at Karlsruhe HfG. - -**Jules LaPlace** is an American creative technologist also based in Berlin. He was previously the CTO of a digital agency in NYC and now also works at VFRAME, developing computer vision for human rights groups. Jules also builds creative software for artists and musicians. +<div class="flex-container"> + <div class="team-member"> + <img src="https://nyc3.digitaloceanspaces.com/megapixels/v1/site/about/assets/adam-harvey-3d.jpg" /> + <h3>Adam Harvey</h3> + <p>is Berlin-based American artist and researcher. His previous projects (CV Dazzle, Stealth Wear, and SkyLift) explore the potential for countersurveillance as artwork. He is the founder of VFRAME (visual forensics software for human rights groups), the recipient of 2 PrototypeFund grants, and is a researcher in residence at Karlsruhe HfG. + <br> + ahprojects.com + </p> + </div> + <div class="team-member"> + <img src="https://nyc3.digitaloceanspaces.com/megapixels/v1/site/about/assets/jules-laplace-3d.jpg" /> + <h3>Jules LaPlace</h3> + <p>is an American creative technologist also based in Berlin. He was previously the CTO of a digital agency in NYC and now also works at VFRAME, developing computer vision for human rights groups. Jules also builds creative software for artists and musicians. + <br> + https://asdf.us + </p> + </div> +</div> diff --git a/site/content/pages/about/press.md b/site/content/pages/about/press.md index 2e6d3423..47e1af52 100644 --- a/site/content/pages/about/press.md +++ b/site/content/pages/about/press.md @@ -17,12 +17,13 @@ authors: Adam Harvey <ul> <li><a href="/about/">About</a></li> <li><a class="current" href="/about/press/">Press</a></li> +<li><a href="/about/credits/">Credits</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> </section> -(list of press articles and images will go here. maybe setup a macro template to use for thumbnail image + press info?) +(TEMPORARY PAGE) - Aug 22, 2018: "Transgender YouTubers had their videos grabbed to train facial recognition software" by James Vincent <https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset>
\ No newline at end of file diff --git a/site/content/pages/about/privacy.md b/site/content/pages/about/privacy.md index 0d908559..e36daf2a 100644 --- a/site/content/pages/about/privacy.md +++ b/site/content/pages/about/privacy.md @@ -17,12 +17,15 @@ authors: Adam Harvey <ul> <li><a href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> +<li><a href="/about/credits/">Credits</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a class="current" href="/about/privacy/">Privacy Policy</a></li> </ul> </section> +(TEMPORARY PAGE) + A summary of our privacy policy is as follows: The MegaPixels site does not use any analytics programs or collect any data besides the necessary IP address of your connection, which are deleted every 30 days and used only for security and to prevent misuse. diff --git a/site/content/pages/about/terms.md b/site/content/pages/about/terms.md index 3217e366..7ae6dac7 100644 --- a/site/content/pages/about/terms.md +++ b/site/content/pages/about/terms.md @@ -18,12 +18,15 @@ authors: Adam Harvey <ul> <li><a href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> +<li><a href="/about/credits/">Credits</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a class="current" href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> </section> +(TEMPORARY PAGE) + (FPO: this is only example text) Last updated: December 04, 2018 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 e7dec0aa..2276e386 100644 --- a/site/content/pages/datasets/50_people_one_question/index.md +++ b/site/content/pages/datasets/50_people_one_question/index.md @@ -1,6 +1,6 @@ ------------ -status: published +status: draft title: 50 People One Question desc: <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 subdesc: People One Question dataset includes ... @@ -23,9 +23,11 @@ authors: Adam Harvey ## 50 People 1 Question - At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio. +(PAGE UNDER DEVELOPMENT) - Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat +At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio. + +Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat {% include 'map.html' %} diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md index 64f7e57d..a01f5bf4 100644 --- a/site/content/pages/datasets/brainwash/index.md +++ b/site/content/pages/datasets/brainwash/index.md @@ -2,8 +2,8 @@ status: published title: Brainwash -desc: Brainwash is a dataset of people from webcams the Brainwash Cafe in San Francisco being used to train face detection algorithms -subdesc: Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" +desc: Brainwash is a dataset of webcam images from the Brainwash Cafe in San Francisco +subdesc: The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection algorithms slug: brainwash cssclass: dataset color: #ffaa00 @@ -33,6 +33,8 @@ authors: Adam Harvey ## Brainwash Dataset +(PAGE UNDER DEVELOPMENT) + *Brainwash* is a face detection dataset created from the Brainwash Cafe's livecam footage including 11,918 images of "everyday life of a busy downtown cafe[^readme]". The images are used to develop face detection algorithms for the "challenging task of detecting people in crowded scenes" and tracking them. Before closing in 2017, Brainwash Cafe was a "cafe and laundromat" located in San Francisco's SoMA district. The cafe published a publicy available livestream from the cafe with a view of the cash register, performance stage, and seating area. diff --git a/site/content/pages/datasets/celeba/index.md b/site/content/pages/datasets/celeba/index.md index 19b0291d..a2669cf6 100644 --- a/site/content/pages/datasets/celeba/index.md +++ b/site/content/pages/datasets/celeba/index.md @@ -1,6 +1,6 @@ ------------ -status: published +status: draft title: CelebA desc: <span style="color:#ffaa00">CelebA</span> is a dataset of people... subdesc: CelebA includes... @@ -23,6 +23,8 @@ authors: Adam Harvey ## CelebA +(PAGE UNDER DEVELOPMENT) + At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio. Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat diff --git a/site/content/pages/datasets/cofw/index.md b/site/content/pages/datasets/cofw/index.md index 3b1cdb2b..d017f405 100644 --- a/site/content/pages/datasets/cofw/index.md +++ b/site/content/pages/datasets/cofw/index.md @@ -1,6 +1,6 @@ ------------ -status: published +status: draft title: Caltech Occluded Faces in The Wild desc: COFW: Caltech Occluded Faces in The Wild slug: cofw @@ -10,7 +10,8 @@ authors: Adam Harvey ------------ -# Caltech Occluded Faces in The Wild + +### sidebar + Years: 1993-1996 + Images: 14,126 @@ -19,9 +20,9 @@ authors: Adam Harvey + Funded by: ODNI, IARPA, Microsoft -<!--header--> +## Caltech Occluded Faces in the Wild - +(PAGE UNDER DEVELOPMENT) 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]. diff --git a/site/content/pages/datasets/lfw/index.md b/site/content/pages/datasets/lfw/index.md index cb326f0b..b803efc5 100644 --- a/site/content/pages/datasets/lfw/index.md +++ b/site/content/pages/datasets/lfw/index.md @@ -2,8 +2,8 @@ status: published title: Labeled Faces in The Wild -desc: Labeled Faces in The Wild (LFW) is a database of face photographs designed for studying the problem of unconstrained face recognition. -subdesc: It includes 13,456 images of 4,432 people's images copied from the Internet during 2002-2004. +desc: Labeled Faces in The Wild (LFW) is the first facial recognition dataset created entirely from online photos +subdesc: 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. image: assets/background.jpg slug: lfw year: 2007 @@ -33,6 +33,8 @@ authors: Adam Harvey ## 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." The LFW dataset includes 13,233 images of 5,749 people that were collected between 2002-2004. LFW is a subset of *Names of Faces* and is part of the first facial recognition training dataset created entirely from images appearing on the Internet. The people appearing in LFW are... diff --git a/site/content/pages/datasets/mars/index.md b/site/content/pages/datasets/mars/index.md index 19f9ced4..864dbe5b 100644 --- a/site/content/pages/datasets/mars/index.md +++ b/site/content/pages/datasets/mars/index.md @@ -2,8 +2,8 @@ status: published title: MARS -desc: <span style="color:#ffaa00">MARS</span> is a dataset of people... -subdesc: MARS includes... +desc: The <span style="color:#99ccee">Motion Analysis and Re-identification Set (MARS)</span> is a dataset is collection of CCTV footage +subdesc: The MARS dataset includes 1,191,003 of people used for training person re-identification algorithms slug: mars cssclass: dataset image: assets/background.jpg @@ -21,7 +21,9 @@ authors: Adam Harvey + Faces: TBD -## 50 MARS +## Motion Analysis and Re-identification Set (MARS) + +(PAGE UNDER DEVELOPMENT) At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio. diff --git a/site/content/pages/research/00_introduction/index.md b/site/content/pages/research/00_introduction/index.md index 9555ca9b..bcb3d57c 100644 --- a/site/content/pages/research/00_introduction/index.md +++ b/site/content/pages/research/00_introduction/index.md @@ -16,6 +16,22 @@ authors: Megapixels + Author: Adam Harvey + +### Motivation + +Ever since government agencies began developing face recognition in the early 1960's, datasets of face images have always been central to developing and validating face recognition technologies. Today, these datasets no longer originate in labs, but instead from family photo albums posted on photo sharing sites, surveillance camera footage from college campuses, search engine queries for celebrities, cafe livestreams, or <a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">videos on YouTube</a>. + +During the last year, hundreds of these facial analysis datasets created "in the wild" have been collected to understand how they contribute to a global supply chain of biometric data that is powering the global facial recognition industry. + +While many of these datasets include public figures such as politicians, athletes, and actors; they also include many non-public figures: digital activists, students, pedestrians, and semi-private shared photo albums are all considered "in the wild" and fair game for research projects. Some images are used with creative commons licenses, yet others were taken in unconstrained scenarios without awareness or consent. At first glance it appears many of the datasets were created for seemingly harmless academic research, but when examined further it becomes clear that they're also used by foreign defense agencies. + +The MegaPixels site is based on an earlier [installation](https://ahprojects.com/megapixels-glassroom) (also supported by Mozilla) at the [Tactical Tech Glassroom](https://theglassroom.org/) in London in 2017; and a commission from the Elevate arts festival curated by Berit Gilma about pedestrian recognition datasets in 2018, and research during [CV Dazzle](https://cvdazzle.com) from 2010-2015. Through the many prototypes, conversations, pitches, PDFs, and false starts this project has endured during the last 5 years, it eventually evolved into something much different than originally imagined. Now, as datasets become increasingly influential in shaping the computational future, it's clear that they must be critically analyzed to understand the biases, shortcomings, funding sources, and contributions to the surveillance industry. However, it's misguided to only criticize these datasets for their flaws without also praising their contribution to society. Without publicly available facial analysis datasets there would be less public discourse, less open-source software, and less peer-reviewed research. Public datasets can indeed become a vital public good for the information economy but as this projects aims to illustrate, many ethical questions arise about consent, intellectual property, surveillance, and privacy. + +<!-- who provided funding to research, development this project understand the role these datasets have played in creating biometric surveillance technologies. --> + + + + Ever since the first computational facial recognition research project by the CIA in the early 1960s, data has always played a vital role in the development of our biometric future. Without facial recognition datasets there would be no facial recognition. Datasets are an indispensable part of any artificial intelligence system because, as Geoffrey Hinton points out: > Our relationship to computers has changed. Instead of programming them, we now show them and they figure it out. - [Geoffrey Hinton](https://www.youtube.com/watch?v=-eyhCTvrEtE) diff --git a/site/public/about/credits/index.html b/site/public/about/credits/index.html new file mode 100644 index 00000000..b7ab8085 --- /dev/null +++ b/site/public/about/credits/index.html @@ -0,0 +1,76 @@ +<!doctype html> +<html> +<head> + <title>MegaPixels</title> + <meta charset="utf-8" /> + <meta name="author" content="Adam Harvey" /> + <meta name="description" content="MegaPixels Press and News" /> + <meta name="referrer" content="no-referrer" /> + <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" /> + <link rel='stylesheet' href='/assets/css/fonts.css' /> + <link rel='stylesheet' href='/assets/css/tabulator.css' /> + <link rel='stylesheet' href='/assets/css/css.css' /> + <link rel='stylesheet' href='/assets/css/leaflet.css' /> + <link rel='stylesheet' href='/assets/css/applets.css' /> +</head> +<body> + <header> + <a class='slogan' href="/"> + <div class='logo'></div> + <div class='site_name'>MegaPixels</div> + </a> + <div class='links'> + <a href="/datasets/">Datasets</a> + <a href="/about/">About</a> + </div> + </header> + <div class="content content-about"> + + <section><h1>Credits</h1> +<section class="about-menu"> +<ul> + <li><a href="/about/">About</a></li> + <li><a href="/about/press/">Press</a></li> + <li><a class="current" href="/about/credits/">Credits</a></li> + <li><a href="/about/disclaimer/">Disclaimer</a></li> + <li><a href="/about/terms/">Terms and Conditions</a></li> + <li><a href="/about/privacy/">Privacy Policy</a></li> +</ul> +</section><h4>Team</h4> +<ul> +<li>Research, concept: Adam Harvey</li> +<li>Site development, visualizations: Jules LaPlace</li> +<li>Assistant researcher: Berit Gilma</li> +<li>Produced in Partnership with Mozilla</li> +</ul> +<h4>Code</h4> +<ul> +<li>This site uses D3 and C2 for visuzations. </li> +<li>Add more here</li> +</ul> +<h4>Data</h4> +<ul> +<li>link to github</li> +<li>how it was gathered</li> +</ul> +</section> + + </div> + <footer> + <div> + <a href="/">MegaPixels.cc</a> + <a href="/about/disclaimer/">Disclaimer</a> + <a href="/about/terms/">Terms of Use</a> + <a href="/about/privacy/">Privacy</a> + <a href="/about/">About</a> + <a href="/about/team/">Team</a> + </div> + <div> + MegaPixels ©2017-19 Adam R. Harvey / + <a href="https://ahprojects.com">ahprojects.com</a> + </div> + </footer> +</body> + +<script src="/assets/js/dist/index.js"></script> +</html>
\ No newline at end of file diff --git a/site/public/about/disclaimer/index.html b/site/public/about/disclaimer/index.html index abbffef6..28588708 100644 --- a/site/public/about/disclaimer/index.html +++ b/site/public/about/disclaimer/index.html @@ -31,11 +31,13 @@ <ul> <li><a href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> +<li><a href="/about/credits/">Credits</a></li> <li><a class="current" href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> -</section></section><section><p>Last updated: December 04, 2018</p> +</section><p>(TEMPORARY PAGE)</p> +<p>Last updated: December 04, 2018</p> <p>The information contained on MegaPixels.cc website (the "Service") is for academic and artistic purposes only.</p> <p>MegaPixels.cc assumes no responsibility for errors or omissions in the contents on the Service.</p> <p>In no event shall MegaPixels.cc be liable for any special, direct, indirect, consequential, or incidental damages or any damages whatsoever, whether in an action of contract, negligence or other tort, arising out of or in connection with the use of the Service or the contents of the Service. MegaPixels.cc reserves the right to make additions, deletions, or modification to the contents on the Service at any time without prior notice.</p> diff --git a/site/public/about/index.html b/site/public/about/index.html index 3cb791be..0ddc1a4b 100644 --- a/site/public/about/index.html +++ b/site/public/about/index.html @@ -31,17 +31,31 @@ <ul> <li><a class="current" href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> +<li><a href="/about/credits/">Credits</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> -</section><p><div style="font-size:20px;line-height:36px">Ever since government agencies began developing face recognition in the early 1960's, datasets of face images have always been central to the development and evaluation of their algorithms. Today, these datasets no longer originate in labs, but instead from family photos albums posted on Flickr, CCTV cameras on college campuses, livestreams at cafes, search engine queries for celebrities, or <a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">videos on YouTube</a>. </div></p><p>While these datasets include many public figures, politicans, athletes, and actors, they also include many non-public figures including digital activists, students, and pedestrians. Some images are used with creative commons licenses, but others were taken in unconstrained scenarios without anyone's awareness or consent. During the last year hundreds of these datasets have been collected to understand how they contribute to a global supply chain of biometric data.</p> -<p>MegaPixels is art and research by <a href="https://ahprojects.com">Adam Harvey</a> about publicly available facial recognition datasets that aims to unravel the stories behind these datasets. During 2019 this site, coded by Jules LaPlace, will publish research reports, visualizations, downloadable statisticds, and interactive tools for searching the datasets.</p> -<p>This project is produced in partnership with <a href="https://mozilla.org">Mozilla</a> who has provided the funding to research the datasets, build the site, and develop tools to help you understand the role these datasets have played in creating biometric surveillance technologies.</p> -<h2>Team</h2> -</section><section class='images'><div class='sideimage'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/about/assets/adam-harvey.jpg' alt='Adam Harvey'><div><p><strong>Adam Harvey</strong> is Berlin-based American artist and researcher. His previous projects (CV Dazzle, Stealth Wear, and SkyLift) explore the potential for countersurveillance as artwork. He is the founder of VFRAME (visual forensics software for human rights groups), the recipient of 2 PrototypeFund awards, and a researcher in residence at Karlsruhe HfG.</p> -</div></div></section><section class='images'><div class='sideimage'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/about/assets/jule s-laplace.jpg' alt='Jules LaPlace'><div><p><strong>Jules LaPlace</strong> is an American creative technologist also based in Berlin. He was previously the CTO of a digital agency in NYC and now also works at VFRAME, developing computer vision for human rights groups. Jules also builds creative software for artists and musicians.</p> -</div></div></section> +</section><p>(PAGE UNDER DEVELOPMENT)</p> +<p><div style="font-size:20px;line-height:36px">MegaPixels is art and research by <a href="https://ahprojects.com">Adam Harvey</a> about facial recognition datasets that aims to unravel their histories, futures, geographies, and meanings. Throughout 2019 this site, coded by Jules LaPlace, will publish research reports, visualizations, raw data, and interactive tools to explore how publicly available facial recognition datasets contribute to a global supply chain of biometric data that powers the global facial recognition industry.</div></p><p>The MegaPixels website is produced in partnership with <a href="https://mozilla.org">Mozilla</a>.</p> +<div class="flex-container"> + <div class="team-member"> + <img src="https://nyc3.digitaloceanspaces.com/megapixels/v1/site/about/assets/adam-harvey-3d.jpg" /> + <h3>Adam Harvey</h3> + <p>is Berlin-based American artist and researcher. His previous projects (CV Dazzle, Stealth Wear, and SkyLift) explore the potential for countersurveillance as artwork. He is the founder of VFRAME (visual forensics software for human rights groups), the recipient of 2 PrototypeFund grants, and is a researcher in residence at Karlsruhe HfG. + <br> + ahprojects.com + </p> + </div> + <div class="team-member"> + <img src="https://nyc3.digitaloceanspaces.com/megapixels/v1/site/about/assets/jules-laplace-3d.jpg" /> + <h3>Jules LaPlace</h3> + <p>is an American creative technologist also based in Berlin. He was previously the CTO of a digital agency in NYC and now also works at VFRAME, developing computer vision for human rights groups. Jules also builds creative software for artists and musicians. + <br> + https://asdf.us + </p> + </div> +</div></section> </div> <footer> diff --git a/site/public/about/press/index.html b/site/public/about/press/index.html index 930fece4..e2e646da 100644 --- a/site/public/about/press/index.html +++ b/site/public/about/press/index.html @@ -31,11 +31,12 @@ <ul> <li><a href="/about/">About</a></li> <li><a class="current" href="/about/press/">Press</a></li> +<li><a href="/about/credits/">Credits</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> -</section><p>(list of press articles and images will go here. maybe setup a macro template to use for thumbnail image + press info?)</p> +</section><p>(TEMPORARY PAGE)</p> <ul> <li>Aug 22, 2018: "Transgender YouTubers had their videos grabbed to train facial recognition software" by James Vincent <a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset</a></li> </ul> diff --git a/site/public/about/privacy/index.html b/site/public/about/privacy/index.html index 12e78bae..f6915d66 100644 --- a/site/public/about/privacy/index.html +++ b/site/public/about/privacy/index.html @@ -31,11 +31,13 @@ <ul> <li><a href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> +<li><a href="/about/credits/">Credits</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a class="current" href="/about/privacy/">Privacy Policy</a></li> </ul> -</section><p>A summary of our privacy policy is as follows:</p> +</section><p>(TEMPORARY PAGE)</p> +<p>A summary of our privacy policy is as follows:</p> <p>The MegaPixels site does not use any analytics programs or collect any data besides the necessary IP address of your connection, which are deleted every 30 days and used only for security and to prevent misuse.</p> <p>The image processing sections of the site do not collect any data whatsoever. All processing takes place in temporary memory (RAM) and then is displayed back to the user over a SSL secured HTTPS connection. It is the sole responsibility of the user whether they discard, by closing the page, or share their analyzed information and any potential consequences that may arise from doing so.</p> <p>A more complete legal version is below:</p> diff --git a/site/public/about/terms/index.html b/site/public/about/terms/index.html index 072b9b88..b86eae88 100644 --- a/site/public/about/terms/index.html +++ b/site/public/about/terms/index.html @@ -31,11 +31,13 @@ <ul> <li><a href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> +<li><a href="/about/credits/">Credits</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a class="current" href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> -</section><p>(FPO: this is only example text)</p> +</section><p>(TEMPORARY PAGE)</p> +<p>(FPO: this is only example text)</p> <p>Last updated: December 04, 2018</p> <p>Please read these Terms and Conditions ("Terms", "Terms and Conditions") carefully before using the MegaPixels website (the "Service") operated by megapixels.cc ("us", "we", or "our").</p> <p>Your access to and use of the Service is conditioned on your acceptance of and compliance with these Terms.</p> diff --git a/site/public/datasets/50_people_one_question/index.html b/site/public/datasets/50_people_one_question/index.html index 25df92b9..3a854d50 100644 --- a/site/public/datasets/50_people_one_question/index.html +++ b/site/public/datasets/50_people_one_question/index.html @@ -28,6 +28,7 @@ <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/50_people_one_question/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span style="color:#ffaa00">People One Question</span> is a dataset of people from an online video series on YouTube and Vimeo used for building facial recogntion algorithms</span></div><div class='hero_subdesc'><span class='bgpad'>People One Question dataset includes ... </span></div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Collected</div><div>TBD</div></div><div><div class='gray'>Published</div><div>TBD</div></div><div><div class='gray'>Images</div><div>TBD</div></div><div><div class='gray'>Faces</div><div>TBD</div></div></div></div><h2>50 People 1 Question</h2> +<p>(PAGE UNDER DEVELOPMENT)</p> <p>At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio.</p> <p>Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat</p> </section><section> diff --git a/site/public/datasets/brainwash/index.html b/site/public/datasets/brainwash/index.html index e5c9da79..ab002c78 100644 --- a/site/public/datasets/brainwash/index.html +++ b/site/public/datasets/brainwash/index.html @@ -4,7 +4,7 @@ <title>MegaPixels</title> <meta charset="utf-8" /> <meta name="author" content="Adam Harvey" /> - <meta name="description" content="Brainwash is a dataset of people from webcams the Brainwash Cafe in San Francisco being used to train face detection algorithms" /> + <meta name="description" content="Brainwash is a dataset of webcam images from the Brainwash Cafe in San Francisco" /> <meta name="referrer" content="no-referrer" /> <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" /> <link rel='stylesheet' href='/assets/css/fonts.css' /> @@ -26,8 +26,9 @@ </header> <div class="content content-dataset"> - <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span style='color: #ffaa00'>Brainwash</span> is a dataset of people from webcams the Brainwash Cafe in San Francisco being used to train face detection algorithms</span></div><div class='hero_subdesc'><span class='bgpad'>Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" + <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span style='color: #ffaa00'>Brainwash</span> is a dataset of webcam images from the Brainwash Cafe in San Francisco</span></div><div class='hero_subdesc'><span class='bgpad'>The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection algorithms </span></div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Collected</div><div>2014</div></div><div><div class='gray'>Published</div><div>2015</div></div><div><div class='gray'>Images</div><div>11,918</div></div><div><div class='gray'>Faces</div><div>91,146</div></div><div><div class='gray'>Created by</div><div>Stanford Department of Computer Science</div></div><div><div class='gray'>Funded by</div><div>Max Planck Center for Visual Computing and Communication</div></div><div><div class='gray'>Resolution</div><div>640x480px</div></div><div><div class='gray'>Size</div><div>4.1GB</div></div><div><div class='gray'>Origin</div><div>Brainwash Cafe, San Franscisco</div></div><div><div class='gray'>Purpose</div><div>Training face detection</div></div><div><div class='gray'>Website</div><div><a href="https://exhibits.stanford.edu/data/catalog/sx925dc9385">stanford.edu</a></div></div><div><div class='gray'>Paper</div><div><a href="http://arxiv.org/abs/1506.04878">End-to-End People Detection in Crowded Scenes</a></div></div></div></div><h2>Brainwash Dataset</h2> +<p>(PAGE UNDER DEVELOPMENT)</p> <p><em>Brainwash</em> is a face detection dataset created from the Brainwash Cafe's livecam footage including 11,918 images of "everyday life of a busy downtown cafe<a class="footnote_shim" name="[^readme]_1"> </a><a href="#[^readme]" class="footnote" title="Footnote 1">1</a>". The images are used to develop face detection algorithms for the "challenging task of detecting people in crowded scenes" and tracking them.</p> <p>Before closing in 2017, Brainwash Cafe was a "cafe and laundromat" located in San Francisco's SoMA district. The cafe published a publicy available livestream from the cafe with a view of the cash register, performance stage, and seating area.</p> <p>Since it's publication by Stanford in 2015, the Brainwash dataset has appeared in several notable research papers. In September 2016 four researchers from the National University of Defense Technology in Changsha, China used the Brainwash dataset for a research study on "people head detection in crowded scenes", concluding that their algorithm "achieves superior head detection performance on the crowded scenes dataset<a class="footnote_shim" name="[^localized_region_context]_1"> </a><a href="#[^localized_region_context]" class="footnote" title="Footnote 2">2</a>". And again in 2017 three researchers at the National University of Defense Technology used Brainwash for a study on object detection noting "the data set used in our experiment is shown in Table 1, which includes one scene of the brainwash dataset<a class="footnote_shim" name="[^replacement_algorithm]_1"> </a><a href="#[^replacement_algorithm]" class="footnote" title="Footnote 3">3</a>".</p> diff --git a/site/public/datasets/celeba/index.html b/site/public/datasets/celeba/index.html index 2977cf2a..024f842f 100644 --- a/site/public/datasets/celeba/index.html +++ b/site/public/datasets/celeba/index.html @@ -28,6 +28,7 @@ <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/celeba/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span style="color:#ffaa00">CelebA</span> is a dataset of people...</span></div><div class='hero_subdesc'><span class='bgpad'>CelebA includes... </span></div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Collected</div><div>TBD</div></div><div><div class='gray'>Published</div><div>TBD</div></div><div><div class='gray'>Images</div><div>TBD</div></div><div><div class='gray'>Faces</div><div>TBD</div></div></div></div><h2>CelebA</h2> +<p>(PAGE UNDER DEVELOPMENT)</p> <p>At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio.</p> <p>Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat</p> </section><section> diff --git a/site/public/datasets/cofw/index.html b/site/public/datasets/cofw/index.html index 8410559f..605a325a 100644 --- a/site/public/datasets/cofw/index.html +++ b/site/public/datasets/cofw/index.html @@ -26,8 +26,9 @@ </header> <div class="content content-"> - <section><h1>Caltech Occluded Faces in The Wild</h1> -</section><section><div class='meta'><div><div class='gray'>Years</div><div>1993-1996</div></div><div><div class='gray'>Images</div><div>14,126</div></div><div><div class='gray'>Identities</div><div>1,199 </div></div><div><div class='gray'>Origin</div><div>Web Searches</div></div><div><div class='gray'>Funded by</div><div>ODNI, IARPA, Microsoft</div></div></div><section><section><!--header--></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/cofw/assets/cofw_index.gif' alt=''></div></section><section><p>COFW is "is designed to benchmark face landmark algorithms in realistic conditions, which include heavy occlusions and large shape variations" [Robust face landmark estimation under occlusion].</p> + <section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Years</div><div>1993-1996</div></div><div><div class='gray'>Images</div><div>14,126</div></div><div><div class='gray'>Identities</div><div>1,199 </div></div><div><div class='gray'>Origin</div><div>Web Searches</div></div><div><div class='gray'>Funded by</div><div>ODNI, IARPA, Microsoft</div></div></div></div><h2>Caltech Occluded Faces in the Wild</h2> +<p>(PAGE UNDER DEVELOPMENT)</p> +<p>COFW is "is designed to benchmark face landmark algorithms in realistic conditions, which include heavy occlusions and large shape variations" [Robust face landmark estimation under occlusion].</p> <p>RESEARCH below this line</p> <blockquote><p>We asked four people with different levels of computer vision knowledge to each collect 250 faces representative of typical real-world images, with the clear goal of challenging computer vision methods. The result is 1,007 images of faces obtained from a variety of sources.</p> diff --git a/site/public/datasets/index.html b/site/public/datasets/index.html index ab9f852d..d9452b11 100644 --- a/site/public/datasets/index.html +++ b/site/public/datasets/index.html @@ -37,18 +37,6 @@ <div class="dataset-list"> - <a href="/datasets/50_people_one_question/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/50_people_one_question/assets/index.jpg)"> - <div class="dataset"> - <span class='title'>50 People One Question</span> - <div class='fields'> - <div class='year visible'><span>2013</span></div> - <div class='purpose'><span>facial landmark estimation in the wild</span></div> - <div class='images'><span> images</span></div> - <div class='identities'><span></span></div> - </div> - </div> - </a> - <a href="/datasets/brainwash/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/index.jpg)"> <div class="dataset"> <span class='title'>Brainwash</span> @@ -61,30 +49,6 @@ </div> </a> - <a href="/datasets/celeba/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/celeba/assets/index.jpg)"> - <div class="dataset"> - <span class='title'>CelebA</span> - <div class='fields'> - <div class='year visible'><span>2015</span></div> - <div class='purpose'><span>face attribute recognition, face detection, and landmark (or facial part) localization</span></div> - <div class='images'><span>202,599 images</span></div> - <div class='identities'><span>10,177 </span></div> - </div> - </div> - </a> - - <a href="/datasets/cofw/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/cofw/assets/index.jpg)"> - <div class="dataset"> - <span class='title'>Caltech Occluded Faces in The Wild</span> - <div class='fields'> - <div class='year visible'><span>2013</span></div> - <div class='purpose'><span>challenging dataset (sunglasses, hats, interaction with objects), supported by IARPA</span></div> - <div class='images'><span>1,007 images</span></div> - <div class='identities'><span></span></div> - </div> - </div> - </a> - <a href="/datasets/lfw/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/index.jpg)"> <div class="dataset"> <span class='title'>Labeled Faces in The Wild</span> diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html index 814cd167..477673e2 100644 --- a/site/public/datasets/lfw/index.html +++ b/site/public/datasets/lfw/index.html @@ -4,7 +4,7 @@ <title>MegaPixels</title> <meta charset="utf-8" /> <meta name="author" content="Adam Harvey" /> - <meta name="description" content="Labeled Faces in The Wild (LFW) is a database of face photographs designed for studying the problem of unconstrained face recognition." /> + <meta name="description" content="Labeled Faces in The Wild (LFW) is the first facial recognition dataset created entirely from online photos" /> <meta name="referrer" content="no-referrer" /> <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" /> <link rel='stylesheet' href='/assets/css/fonts.css' /> @@ -26,7 +26,7 @@ </header> <div class="content content-"> - <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span style='color: #ff0000'>Labeled Faces in The Wild</span> (LFW) is a database of face photographs designed for studying the problem of unconstrained face recognition.</span></div><div class='hero_subdesc'><span class='bgpad'>It includes 13,456 images of 4,432 people's images copied from the Internet during 2002-2004. + <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span style='color: #ff0000'>Labeled Faces in The Wild</span> (LFW) is the first facial recognition dataset created entirely from online photos</span></div><div class='hero_subdesc'><span class='bgpad'>It includes 13,456 images of 4,432 people's images copied from the Internet during 2002-2004 and is the most frequently used dataset in the world for benchmarking face recognition algorithms. </span></div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Created</div><div>2002 – 2004</div></div><div><div class='gray'>Images</div><div>13,233</div></div><div><div class='gray'>Identities</div><div>5,749</div></div><div><div class='gray'>Origin</div><div>Yahoo! News Images</div></div><div><div class='gray'>Used by</div><div>Facebook, Google, Microsoft, Baidu, Tencent, SenseTime, Face++, CIA, NSA, IARPA</div></div><div><div class='gray'>Website</div><div><a href="http://vis-www.cs.umass.edu/lfw">umass.edu</a></div></div></div><ul> <li>There are about 3 men for every 1 woman in the LFW dataset<a class="footnote_shim" name="[^lfw_www]_1"> </a><a href="#[^lfw_www]" class="footnote" title="Footnote 1">1</a></li> <li>The person with the most images is <a href="http://vis-www.cs.umass.edu/lfw/person/George_W_Bush_comp.html">George W. Bush</a> with 530</li> @@ -37,6 +37,7 @@ <li>* denotes partial funding for related research</li> </ul> </div><h2>Labeled Faces in the Wild</h2> +<p>(PAGE UNDER DEVELOPMENT)</p> <p><em>Labeled Faces in The Wild</em> (LFW) is "a database of face photographs designed for studying the problem of unconstrained face recognition<a class="footnote_shim" name="[^lfw_www]_2"> </a><a href="#[^lfw_www]" class="footnote" title="Footnote 1">1</a>. It is used to evaluate and improve the performance of facial recognition algorithms in academic, commercial, and government research. According to BiometricUpdate.com<a class="footnote_shim" name="[^lfw_pingan]_1"> </a><a href="#[^lfw_pingan]" class="footnote" title="Footnote 3">3</a>, LFW is "the most widely used evaluation set in the field of facial recognition, LFW attracts a few dozen teams from around the globe including Google, Facebook, Microsoft Research Asia, Baidu, Tencent, SenseTime, Face++ and Chinese University of Hong Kong."</p> <p>The LFW dataset includes 13,233 images of 5,749 people that were collected between 2002-2004. LFW is a subset of <em>Names of Faces</em> and is part of the first facial recognition training dataset created entirely from images appearing on the Internet. The people appearing in LFW are...</p> <p>The <em>Names and Faces</em> dataset was the first face recognition dataset created entire from online photos. However, <em>Names and Faces</em> and <em>LFW</em> are not the first face recognition dataset created entirely "in the wild". That title belongs to the <a href="/datasets/ucd_faces/">UCD dataset</a>. Images obtained "in the wild" means using an image without explicit consent or awareness from the subject or photographer.</p> diff --git a/site/public/datasets/mars/index.html b/site/public/datasets/mars/index.html index 66084e15..bfad52a3 100644 --- a/site/public/datasets/mars/index.html +++ b/site/public/datasets/mars/index.html @@ -4,7 +4,7 @@ <title>MegaPixels</title> <meta charset="utf-8" /> <meta name="author" content="Adam Harvey" /> - <meta name="description" content="MARS is a dataset of people..." /> + <meta name="description" content="The Motion Analysis and Re-identification Set (MARS) is a dataset is collection of CCTV footage " /> <meta name="referrer" content="no-referrer" /> <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" /> <link rel='stylesheet' href='/assets/css/fonts.css' /> @@ -26,8 +26,9 @@ </header> <div class="content content-dataset"> - <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/mars/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span style="color:#ffaa00">MARS</span> is a dataset of people...</span></div><div class='hero_subdesc'><span class='bgpad'>MARS includes... -</span></div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Collected</div><div>TBD</div></div><div><div class='gray'>Published</div><div>TBD</div></div><div><div class='gray'>Images</div><div>TBD</div></div><div><div class='gray'>Faces</div><div>TBD</div></div></div></div><h2>50 MARS</h2> + <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/mars/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'>The <span style="color:#99ccee">Motion Analysis and Re-identification Set (MARS)</span> is a dataset is collection of CCTV footage </span></div><div class='hero_subdesc'><span class='bgpad'>The MARS dataset includes 1,191,003 of people used for training person re-identification algorithms +</span></div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Collected</div><div>TBD</div></div><div><div class='gray'>Published</div><div>TBD</div></div><div><div class='gray'>Images</div><div>TBD</div></div><div><div class='gray'>Faces</div><div>TBD</div></div></div></div><h2>Motion Analysis and Re-identification Set (MARS)</h2> +<p>(PAGE UNDER DEVELOPMENT)</p> <p>At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio.</p> <p>Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat</p> </section><section> diff --git a/site/public/research/00_introduction/index.html b/site/public/research/00_introduction/index.html index 95735b5a..5c536dc4 100644 --- a/site/public/research/00_introduction/index.html +++ b/site/public/research/00_introduction/index.html @@ -41,7 +41,17 @@ </div> </section> - <section><div class='meta'><div><div class='gray'>Posted</div><div>Dec. 15</div></div><div><div class='gray'>Author</div><div>Adam Harvey</div></div></div><section><section><p>Ever since the first computational facial recognition research project by the CIA in the early 1960s, data has always played a vital role in the development of our biometric future. Without facial recognition datasets there would be no facial recognition. Datasets are an indispensable part of any artificial intelligence system because, as Geoffrey Hinton points out:</p> + <section><div class='meta'><div><div class='gray'>Posted</div><div>Dec. 15</div></div><div><div class='gray'>Author</div><div>Adam Harvey</div></div></div><section><section><h3>Motivation</h3> +<p>Ever since government agencies began developing face recognition in the early 1960's, datasets of face images have always been central to developing and validating face recognition technologies. Today, these datasets no longer originate in labs, but instead from family photo albums posted on photo sharing sites, surveillance camera footage from college campuses, search engine queries for celebrities, cafe livestreams, or <a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">videos on YouTube</a>.</p> +<p>During the last year, hundreds of these facial analysis datasets created "in the wild" have been collected to understand how they contribute to a global supply chain of biometric data that is powering the global facial recognition industry.</p> +<p>While many of these datasets include public figures such as politicians, athletes, and actors; they also include many non-public figures: digital activists, students, pedestrians, and semi-private shared photo albums are all considered "in the wild" and fair game for research projects. Some images are used with creative commons licenses, yet others were taken in unconstrained scenarios without awareness or consent. At first glance it appears many of the datasets were created for seemingly harmless academic research, but when examined further it becomes clear that they're also used by foreign defense agencies.</p> +<p>The MegaPixels site is based on an earlier <a href="https://ahprojects.com/megapixels-glassroom">installation</a> (also supported by Mozilla) at the <a href="https://theglassroom.org/">Tactical Tech Glassroom</a> in London in 2017; and a commission from the Elevate arts festival curated by Berit Gilma about pedestrian recognition datasets in 2018, and research during <a href="https://cvdazzle.com">CV Dazzle</a> from 2010-2015. Through the many prototypes, conversations, pitches, PDFs, and false starts this project has endured during the last 5 years, it eventually evolved into something much different than originally imagined. Now, as datasets become increasingly influential in shaping the computational future, it's clear that they must be critically analyzed to understand the biases, shortcomings, funding sources, and contributions to the surveillance industry. However, it's misguided to only criticize these datasets for their flaws without also praising their contribution to society. Without publicly available facial analysis datasets there would be less public discourse, less open-source software, and less peer-reviewed research. Public datasets can indeed become a vital public good for the information economy but as this projects aims to illustrate, many ethical questions arise about consent, intellectual property, surveillance, and privacy.</p> +<!-- who provided funding to research, development this project understand the role these datasets have played in creating biometric surveillance technologies. --> + + + + +<p>Ever since the first computational facial recognition research project by the CIA in the early 1960s, data has always played a vital role in the development of our biometric future. Without facial recognition datasets there would be no facial recognition. Datasets are an indispensable part of any artificial intelligence system because, as Geoffrey Hinton points out:</p> <blockquote><p>Our relationship to computers has changed. Instead of programming them, we now show them and they figure it out. - <a href="https://www.youtube.com/watch?v=-eyhCTvrEtE">Geoffrey Hinton</a></p> </blockquote> <p>Algorithms learn from datasets. And we program algorithms by building datasets. But datasets aren't like code. There's no programming language made of data except for the data itself.</p> |
