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29 files changed, 73 insertions, 70 deletions
diff --git a/site/assets/css/css.css b/site/assets/css/css.css index 47106dd9..a0f9519b 100644 --- a/site/assets/css/css.css +++ b/site/assets/css/css.css @@ -491,6 +491,7 @@ 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/disclaimer.md b/site/content/pages/about/disclaimer.md index 97edc461..314675ee 100644 --- a/site/content/pages/about/disclaimer.md +++ b/site/content/pages/about/disclaimer.md @@ -23,9 +23,7 @@ authors: Adam Harvey </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..deb4c0e7 100644 --- a/site/content/pages/about/index.md +++ b/site/content/pages/about/index.md @@ -23,17 +23,28 @@ authors: Adam Harvey </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">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 face recognition technology. Today, these datasets no longer originate in labs, but instead from family photo albums posted on social media sites, CCTV 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>. </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. +While many of these datasets include public figures such as politicans, athletes, and actors; they also include many non-public figures including digital activists, students, pedestrians, and people's semi-private shared photo albums. 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 studies, but when examined further it becomes clear that they're also used by defense contractors in foreign countries. -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. +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 helping to power the global facial recognition industry. +MegaPixels is art and research by <a href="https://ahprojects.com">Adam Harvey</a> about publicly available facial recognition datasets that aims to unravel their histories, futures, geographies, and contents. Throughout 2019 this site, coded by Jules LaPlace, will publish research reports, visualizations, downloadable statistics, and interactive tools for searching the datasets. -## Team +The MegaPixels website is produced in partnership with [Mozilla](https://mozilla.org) who 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. - **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. +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 about the facial recognition datasets; and a commission from the Elevate arts festival curated by Berit Gilma about pedestrian recognition datasets. -**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. + +### MegaPixels Team + + **Adam Harvey** is Berlin-based American artist and researcher. His previous projects ([CV Dazzle](https://ahprojects.com/cvdazzle), [Stealth Wear](https://ahprojects.com/stealth-wear), and [SkyLift](https://ahprojects.com/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 is a researcher in residence at Karlsruhe HfG. <br>[ahprojects.com](https://ahprojects.com) + +**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.<br>[asdf.us](https://asdf.us) + + +### Additional Researchers + +Additional research by Berit Gilma.
\ No newline at end of file diff --git a/site/content/pages/about/press.md b/site/content/pages/about/press.md index 2e6d3423..759400e8 100644 --- a/site/content/pages/about/press.md +++ b/site/content/pages/about/press.md @@ -23,6 +23,6 @@ authors: Adam Harvey </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..b42ccb21 100644 --- a/site/content/pages/about/privacy.md +++ b/site/content/pages/about/privacy.md @@ -23,6 +23,8 @@ authors: Adam Harvey </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..40653292 100644 --- a/site/content/pages/about/terms.md +++ b/site/content/pages/about/terms.md @@ -24,6 +24,8 @@ authors: Adam Harvey </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..4812e55d 100644 --- a/site/content/pages/datasets/brainwash/index.md +++ b/site/content/pages/datasets/brainwash/index.md @@ -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..b07c0e4b 100644 --- a/site/content/pages/datasets/lfw/index.md +++ b/site/content/pages/datasets/lfw/index.md @@ -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..93edaeea 100644 --- a/site/content/pages/datasets/mars/index.md +++ b/site/content/pages/datasets/mars/index.md @@ -21,7 +21,9 @@ authors: Adam Harvey + Faces: TBD -## 50 MARS +## 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/public/about/disclaimer/index.html b/site/public/about/disclaimer/index.html index abbffef6..25281a16 100644 --- a/site/public/about/disclaimer/index.html +++ b/site/public/about/disclaimer/index.html @@ -35,7 +35,8 @@ <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..15c4a831 100644 --- a/site/public/about/index.html +++ b/site/public/about/index.html @@ -35,13 +35,18 @@ <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">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 face recognition technology. Today, these datasets no longer originate in labs, but instead from family photo albums posted on social media sites, CCTV 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>. </div></p><p>While many of these datasets include public figures such as politicans, athletes, and actors; they also include many non-public figures including digital activists, students, pedestrians, and people's semi-private shared photo albums. 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 studies, but when examined further it becomes clear that they're also used by defense contractors in foreign countries.</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 helping to power the global facial recognition industry.</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 their histories, futures, geographies, and contents. Throughout 2019 this site, coded by Jules LaPlace, will publish research reports, visualizations, downloadable statistics, and interactive tools for searching the datasets.</p> +<p>The MegaPixels website is produced in partnership with <a href="https://mozilla.org">Mozilla</a> who 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> +<p>The MegaPixels site is based on an <a href="https://ahprojects.com/megapixels-glassroom">earlier installation</a>, also supported by Mozilla, at the <a href="https://theglassroom.org/">Tactical Tech Glassroom</a> in London about the facial recognition datasets; and a commission from the Elevate arts festival curated by Berit Gilma about pedestrian recognition datasets.</p> +<h3>MegaPixels Team</h3> +</section><section class='images'><div class='sideimage'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/about/assets/adam-harvey-3d.jpg' alt='Adam Harvey'><div><p><strong>Adam Harvey</strong> is Berlin-based American artist and researcher. His previous projects (<a href="https://ahprojects.com/cvdazzle">CV Dazzle</a>, <a href="https://ahprojects.com/stealth-wear">Stealth Wear</a>, and <a href="https://ahprojects.com/skylift">SkyLift</a>) 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 is a researcher in residence at Karlsruhe HfG. <br><a href="https://ahprojects.com">ahprojects.com</a></p> +</div></div></section><section class='images'><div class='sideimage'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/about/assets/jules-laplace-3d.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.<br><a href="https://asdf.us">asdf.us</a></p> +</div></div></section><section><h3>Additional Researchers</h3> +<p>Additional research by Berit Gilma.</p> +</section> </div> <footer> diff --git a/site/public/about/press/index.html b/site/public/about/press/index.html index 930fece4..23daf552 100644 --- a/site/public/about/press/index.html +++ b/site/public/about/press/index.html @@ -35,7 +35,7 @@ <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..35bda6c6 100644 --- a/site/public/about/privacy/index.html +++ b/site/public/about/privacy/index.html @@ -35,7 +35,8 @@ <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..100f03d5 100644 --- a/site/public/about/terms/index.html +++ b/site/public/about/terms/index.html @@ -35,7 +35,8 @@ <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..9cf2db0d 100644 --- a/site/public/datasets/brainwash/index.html +++ b/site/public/datasets/brainwash/index.html @@ -28,6 +28,7 @@ <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" </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..4fbd06a5 100644 --- a/site/public/datasets/lfw/index.html +++ b/site/public/datasets/lfw/index.html @@ -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..62f8847e 100644 --- a/site/public/datasets/mars/index.html +++ b/site/public/datasets/mars/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/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> +</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>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> |
