From b3bfb2f6f34f5065658e4c0ef289791ab24e5ae2 Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Tue, 16 Apr 2019 17:24:25 +0200 Subject: wide sidebar --- megapixels/app/site/parser.py | 6 +++++- site/assets/css/css.css | 3 ++- site/content/pages/datasets/uccs/index.md | 10 +++------- site/public/datasets/lfw/index.html | 2 +- site/public/datasets/uccs/index.html | 31 ++++++++++++++++--------------- 5 files changed, 27 insertions(+), 25 deletions(-) diff --git a/megapixels/app/site/parser.py b/megapixels/app/site/parser.py index 6b71e041..aa2ddcda 100644 --- a/megapixels/app/site/parser.py +++ b/megapixels/app/site/parser.py @@ -59,10 +59,14 @@ def parse_markdown(metadata, sections, s3_path, skip_h1=False): if 'sidebar' not in section.lower(): current_group.append(section) in_stats = True + if 'end sidebar' in section.lower(): + groups.append(format_section(current_group, s3_path, 'right-sidebar', tag='div')) + current_group = [] + in_stats = False elif in_stats and not section.strip().startswith('## ') and 'end sidebar' not in section.lower(): current_group.append(section) elif in_stats and section.strip().startswith('## ') or 'end sidebar' in section.lower(): - current_group = [format_section(current_group, s3_path, 'left-sidebar', tag='div')] + current_group = [format_section(current_group, s3_path, 'right-sidebar', tag='div')] if 'end sidebar' not in section.lower(): current_group.append(section) in_stats = False diff --git a/site/assets/css/css.css b/site/assets/css/css.css index 1c7b8859..774f34f8 100644 --- a/site/assets/css/css.css +++ b/site/assets/css/css.css @@ -318,7 +318,8 @@ p.subp{ .right-sidebar { float: right; width: 240px; - margin: 75px 20px 20px 20px; + margin: 0px 20px 20px 20px; + padding-top: 12px; padding-left: 20px; border-left: 1px solid #333; font-family: 'Roboto'; diff --git a/site/content/pages/datasets/uccs/index.md b/site/content/pages/datasets/uccs/index.md index 767f8220..67c53893 100644 --- a/site/content/pages/datasets/uccs/index.md +++ b/site/content/pages/datasets/uccs/index.md @@ -15,18 +15,16 @@ authors: Adam Harvey ------------ +## UnConstrained College Students + ### sidebar ### end sidebar -## UnConstrained College Students - UnConstrained College Students (UCCS) is a dataset of long-range surveillance photos captured at University of Colorado Colorado Springs. According to the authors of two papers associated with the dataset, over 1,700 students and pedestrians were "photographed using a long-range high-resolution surveillance camera without their knowledge" [^funding_uccs]. In this investigation, we examine the funding sources, contents of the dataset, photo EXIF data, and publicy available research project citations. According to the author's of the the UnConstrained College Students dataset it is primarliy used for research and development of "face detection and recognition research towards surveillance applications that are becoming more popular and more required nowadays, and where no automatic recognition algorithm has proven to be useful yet." Applications of this technology include usage by defense and intelligence agencies, who were also the primary funding sources of the UCCS dataset. - - -In the two papers associated with the release of the UCCS datasaet ([Unconstrained Face Detection and Open-Set Face Recognition Challenge](https://www.semanticscholar.org/paper/Unconstrained-Face-Detection-and-Open-Set-Face-G%C3%BCnther-Hu/d4f1eb008eb80595bcfdac368e23ae9754e1e745) and [Large Scale Unconstrained Open Set Face Database](https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1)), the researchers disclosed their funding sources as ODNI (United States Office of Director of National Intelligence), IARPA (Intelligence Advance Research Projects Activity), ONR MURI (Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative), Army SBIR (Small Business Innovation Research), SOCOM SBIR (Special Operations Command and Small Business Innovation Research), and the National Science Foundation. Further, UCCS's VAST site explicity [states](https://vast.uccs.edu/project/iarpa-janus/) they are part of the [IARPA Janus](https://www.iarpa.gov/index.php/research-programs/janus), a face recognition project developed to serve the needs of national intelligence interests. +In the two papers associated with the release of the UCCS dataset ([Unconstrained Face Detection and Open-Set Face Recognition Challenge](https://www.semanticscholar.org/paper/Unconstrained-Face-Detection-and-Open-Set-Face-G%C3%BCnther-Hu/d4f1eb008eb80595bcfdac368e23ae9754e1e745) and [Large Scale Unconstrained Open Set Face Database](https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1)), the researchers disclosed their funding sources as ODNI (United States Office of Director of National Intelligence), IARPA (Intelligence Advance Research Projects Activity), ONR MURI (Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative), Army SBIR (Small Business Innovation Research), SOCOM SBIR (Special Operations Command and Small Business Innovation Research), and the National Science Foundation. Further, UCCS's VAST site explicity [states](https://vast.uccs.edu/project/iarpa-janus/) they are part of the [IARPA Janus](https://www.iarpa.gov/index.php/research-programs/janus), a face recognition project developed to serve the needs of national intelligence interests. ![caption: Location on campus where students were unknowingly photographed with a telephoto lens to be used for defense and intelligence agency funded research on face recognition. Image: Google Maps](assets/uccs_map_aerial.jpg) @@ -122,8 +120,6 @@ If you attended University of Colorado Colorado Springs and were captured by the {% include 'cite_our_work.html' %} -{% include 'last_updated.html' %} - ### Footnotes [^funding_sb]: Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013. diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html index 2d91b065..60a6bf0e 100644 --- a/site/public/datasets/lfw/index.html +++ b/site/public/datasets/lfw/index.html @@ -27,7 +27,7 @@
Labeled Faces in The Wild (LFW) is the first facial recognition dataset created entirely from online photos
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. -
+
Published
2007
diff --git a/site/public/datasets/uccs/index.html b/site/public/datasets/uccs/index.html index 4a0dfb5e..1d76de3a 100644 --- a/site/public/datasets/uccs/index.html +++ b/site/public/datasets/uccs/index.html @@ -4,7 +4,7 @@ MegaPixels - + @@ -26,8 +26,9 @@
-
UnConstrained College Students is a dataset of long-range surveillance photos of students at University of Colorado in Colorado Springs
The UnConstrained College Students dataset includes 16,149 images and 1,732 identities of subjects on University of Colorado Colorado Springs campus and is used for making face recognition and face detection algorithms -
+
UnConstrained College Students is a dataset of long-range surveillance photos of students on University of Colorado in Colorado Springs campus
The UnConstrained College Students dataset includes 16,149 images of 1,732 students, faculty, and pedestrians and is used for developing face recognition and face detection algorithms +

UnConstrained College Students

+
Published
2016
@@ -48,15 +49,14 @@
Website
-

UnConstrained College Students

-

[ page under development ]

-

UnConstrained College Students (UCCS) is a dataset of long-range surveillance photos captured at University of Colorado Colorado Springs. According to the authors of two papers associated with the dataset, subjects were "photographed using a long-range high-resolution surveillance camera without their knowledge" 2. To create the dataset, the researchers used a Canon 7D digital camera fitted with a Sigma 800mm telephoto lens and photographed students 150–200m away through their office window. Photos were taken during the morning and afternoon while students were walking to and from classes. The primary uses of this dataset are to train, validate, and build recognition and face detection algorithms for realistic surveillance scenarios.

-

What makes the UCCS dataset unique is that it includes the highest resolution images of any publicly available face recognition dataset discovered so far (18MP), that it was captured on a campus without consent or awareness using a long-range telephoto lens, and that it was funded by United States defense and intelligence agencies.

-

Combined funding sources for the creation of the initial and final release of the dataset include ODNI (Office of Director of National Intelligence), IARPA (Intelligence Advance Research Projects Activity), ONR MURI (Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative), Army SBIR (Small Business Innovation Research), SOCOM SBIR (Special Operations Command and Small Business Innovation Research), and the National Science Foundation. 1 2

-

In 2017 the UCCS face dataset was used for a defense and intelligence agency funded face recognition challenge at the International Joint Biometrics Conference in Denver, CO. And in 2018 the dataset was used for the 2nd Unconstrained Face Detection and Open Set Recognition Challenge at the European Computer Vision Conference (ECCV) in Munich, Germany. Additional research projects that have used the UCCS dataset are included below in the list of verified citations.

-

UCCS is part of the IARAP Janus team https://vast.uccs.edu/project/iarpa-janus/

-

https://arxiv.org/abs/1708.02337

-
+

UnConstrained College Students (UCCS) is a dataset of long-range surveillance photos captured at University of Colorado Colorado Springs. According to the authors of two papers associated with the dataset, over 1,700 students and pedestrians were "photographed using a long-range high-resolution surveillance camera without their knowledge" 2. In this investigation, we examine the funding sources, contents of the dataset, photo EXIF data, and publicy available research project citations.

+

According to the author's of the the UnConstrained College Students dataset it is primarliy used for research and development of "face detection and recognition research towards surveillance applications that are becoming more popular and more required nowadays, and where no automatic recognition algorithm has proven to be useful yet." Applications of this technology include usage by defense and intelligence agencies, who were also the primary funding sources of the UCCS dataset.

+

In the two papers associated with the release of the UCCS dataset (Unconstrained Face Detection and Open-Set Face Recognition Challenge and Large Scale Unconstrained Open Set Face Database), the researchers disclosed their funding sources as ODNI (United States Office of Director of National Intelligence), IARPA (Intelligence Advance Research Projects Activity), ONR MURI (Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative), Army SBIR (Small Business Innovation Research), SOCOM SBIR (Special Operations Command and Small Business Innovation Research), and the National Science Foundation. Further, UCCS's VAST site explicity states they are part of the IARPA Janus, a face recognition project developed to serve the needs of national intelligence interests.

+
Location on campus where students were unknowingly photographed with a telephoto lens to be used for defense and intelligence agency funded research on face recognition. Image: Google Maps
Location on campus where students were unknowingly photographed with a telephoto lens to be used for defense and intelligence agency funded research on face recognition. Image: Google Maps

The UCCS dataset includes the highest resolution images of any publicly available face recognition dataset discovered so far (18MP) and was, as of 2018, the "largest surveillance FR benchmark in the public domain." 3 To create the dataset, the researchers used a Canon 7D digital camera fitted with a Sigma 800mm telephoto lens and photographed students from a distance of 150–200m through their office window. Photos were taken during the morning and afternoon while students were walking to and from classes. According to an analysis of the EXIF data embedded in the photos, nearly half of the 16,149 photos were taken on Tuesdays. The most popular time was during lunch break. All of the photos were taken during the spring semester in 2012 and 2013 but the dataset was not publicy released until 2016.

+

In 2017 the UCCS face dataset was used for a defense and intelligence agency funded face recognition challenge at the International Joint Biometrics Conference in Denver, CO. And in 2018 the dataset was again used for the 2nd Unconstrained Face Detection and Open Set Recognition Challenge at the European Computer Vision Conference (ECCV) in Munich, Germany. Additional research projects that have used the UCCS dataset are included below in the list of verified citations.

+

As of April 15, 2019, the UCCS dataset is no longer available for public download. During the three years it was publicly available (2016-2019) the UCCS dataset apepared in at least 5 publicly available research papers including verified usage from University of Notre Dame (US), Beihang University (China), Beckman Institute (US), Queen Mary University of London (UK), Carnegie Mellon University (US),Karlsruhe Institute of Technology (DE), and Vision Semantics Ltd (UK) who lists the UK Ministry of Defence and Metropolitan Police as partners.

+

To show the types of face images used in the UCCS student dataset while protecting their individual privacy, a generative adversarial network was used to interpolate between identities in the dataset. The image below shows a generative adversarial network trained on the UCCS face bounding box areas from 16,000 images and over 90,000 face regions.

+
GAN generated approximations of students in the UCCS dataset. © megapixels.cc 2018
GAN generated approximations of students in the UCCS dataset. © megapixels.cc 2018

Who used UCCS?

@@ -212,7 +212,7 @@

Location

The location of the camera and subjects can confirmed using several visual cues in the dataset images: the unique pattern of the sidewalk that is only used on the UCCS Pedestrian Spine near the West Lawn, the two UCCS sign poles with matching graphics still visible in Google Street View, the no parking sign and directionality of its arrow, the back of street sign next to it, the slight bend in the sidewalk, the presence of cars passing in the background of the image, and the far wall of the parking garage all match images in the dataset. The original papers also provides another clue: a picture of the camera inside the office that was used to create the dataset. The window view in this image provides another match for the brick pattern on the north facade of the Kraember Family Library and the green metal fence along the sidewalk. View the location on Google Maps

-
Location on campus where students were unknowingly photographed with a telephoto lens to be used for defense and intelligence agency funded research on face recognition. Image: Google Maps
Location on campus where students were unknowingly photographed with a telephoto lens to be used for defense and intelligence agency funded research on face recognition. Image: Google Maps
3D view showing the angle of view of the surveillance camera used for UCCS dataset. Image: Google Maps
3D view showing the angle of view of the surveillance camera used for UCCS dataset. Image: Google Maps

Funding

+
3D view showing the angle of view of the surveillance camera used for UCCS dataset. Image: Google Maps
3D view showing the angle of view of the surveillance camera used for UCCS dataset. Image: Google Maps

Funding

The UnConstrained College Students dataset is associated with two main research papers: "Large Scale Unconstrained Open Set Face Database" and "Unconstrained Face Detection and Open-Set Face Recognition Challenge". Collectively, these papers and the creation of the dataset have received funding from the following organizations:

  • ONR (Office of Naval Research) MURI (The Department of Defense Multidisciplinary University Research Initiative) grant N00014-08-1-0638
    • @@ -250,8 +250,9 @@ }

    -

References

  • a

    Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013.

    -
  • ab

    Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3.

    +

References

  • Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013.

    +
  • a

    Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3.

    +
  • a

    "Surveillance Face Recognition Challenge". SemanticScholar

-- cgit v1.2.3-70-g09d2 From 92cdcf6e684a2de2846865e99281d939cc3ecd5a Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Tue, 16 Apr 2019 17:26:54 +0200 Subject: fix the sidebar --- .../pages/datasets/50_people_one_question/index.md | 4 +- site/content/pages/datasets/afad/index.md | 4 +- site/content/pages/datasets/brainwash/index.md | 4 +- site/content/pages/datasets/caltech_10k/index.md | 4 +- site/content/pages/datasets/celeba/index.md | 4 +- site/content/pages/datasets/cofw/index.md | 4 +- site/content/pages/datasets/duke_mtmc/index.md | 4 +- site/content/pages/datasets/feret/index.md | 4 +- .../pages/datasets/hrt_transgender/index.md | 4 +- site/content/pages/datasets/lfpw/index.md | 4 +- site/content/pages/datasets/lfw/index.md | 4 +- site/content/pages/datasets/market_1501/index.md | 4 +- site/content/pages/datasets/msceleb/index.md | 4 +- .../pages/datasets/oxford_town_centre/index.md | 4 +- site/content/pages/datasets/pipa/index.md | 4 +- site/content/pages/datasets/pubfig/index.md | 4 +- site/content/pages/datasets/vgg_face2/index.md | 3 +- site/content/pages/datasets/viper/index.md | 4 +- .../pages/datasets/youtube_celebrities/index.md | 3 +- .../datasets/50_people_one_question/index.html | 6 +-- site/public/datasets/afad/index.html | 6 +-- site/public/datasets/brainwash/index.html | 6 +-- site/public/datasets/caltech_10k/index.html | 6 +-- site/public/datasets/celeba/index.html | 6 +-- site/public/datasets/cofw/index.html | 6 +-- site/public/datasets/duke_mtmc/index.html | 15 ++++-- site/public/datasets/feret/index.html | 62 +++++++++++++++++++--- site/public/datasets/hrt_transgender/index.html | 6 +-- site/public/datasets/index.html | 24 +++++++++ site/public/datasets/lfpw/index.html | 6 +-- site/public/datasets/lfw/index.html | 6 +-- site/public/datasets/market_1501/index.html | 6 +-- site/public/datasets/msceleb/index.html | 6 +-- site/public/datasets/oxford_town_centre/index.html | 6 +-- site/public/datasets/pipa/index.html | 6 +-- site/public/datasets/pubfig/index.html | 6 +-- site/public/datasets/uccs/index.html | 4 +- site/public/datasets/vgg_face2/index.html | 6 +-- site/public/datasets/viper/index.html | 6 +-- .../public/datasets/youtube_celebrities/index.html | 4 +- todo.md | 1 - 41 files changed, 178 insertions(+), 102 deletions(-) diff --git a/site/content/pages/datasets/50_people_one_question/index.md b/site/content/pages/datasets/50_people_one_question/index.md index 09406f43..8b7fb931 100644 --- a/site/content/pages/datasets/50_people_one_question/index.md +++ b/site/content/pages/datasets/50_people_one_question/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## 50 People 1 Question + ### sidebar ### end sidebar -## 50 People 1 Question - [ page under development ] {% include 'dashboard.html' %} \ No newline at end of file diff --git a/site/content/pages/datasets/afad/index.md b/site/content/pages/datasets/afad/index.md index c941cbc6..755506d8 100644 --- a/site/content/pages/datasets/afad/index.md +++ b/site/content/pages/datasets/afad/index.md @@ -10,11 +10,11 @@ authors: Adam Harvey ------------ +## Asian Face Age Dataset + ### sidebar ### end sidebar -## Asian Face Age Dataset - [ page under development ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md index 6bb7f287..156b02c7 100644 --- a/site/content/pages/datasets/brainwash/index.md +++ b/site/content/pages/datasets/brainwash/index.md @@ -14,11 +14,11 @@ authors: Adam Harvey ------------ +## Brainwash Dataset + ### sidebar ### end sidebar -## Brainwash Dataset - *Brainwash* is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 11,918 images of "everyday life of a busy downtown cafe"[^readme] captured at 100 second intervals throught the entire day. Brainwash dataset was captured during 3 days in 2014: October 27, November 13, and November 24. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com.[^end_to_end] Brainwash is not a widely used dataset but since its publication by Stanford University in 2015, it has notably appeared in several research papers from the National University of Defense Technology in Changsha, China. In 2016 and in 2017 researchers there conducted studies on detecting people's heads in crowded scenes for the purpose of surveillance. [^localized_region_context] [^replacement_algorithm] diff --git a/site/content/pages/datasets/caltech_10k/index.md b/site/content/pages/datasets/caltech_10k/index.md index b69dbe43..db2383c7 100644 --- a/site/content/pages/datasets/caltech_10k/index.md +++ b/site/content/pages/datasets/caltech_10k/index.md @@ -11,11 +11,11 @@ authors: Adam Harvey ------------ +## Caltech 10K Faces Dataset + ### sidebar ### end sidebar -## Caltech 10K Faces Dataset - [ page under development ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/celeba/index.md b/site/content/pages/datasets/celeba/index.md index 9cdbcad9..3f3aea79 100644 --- a/site/content/pages/datasets/celeba/index.md +++ b/site/content/pages/datasets/celeba/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## CelebA Dataset + ### sidebar ### end sidebar -## CelebA Dataset - [ PAGE UNDER DEVELOPMENT ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/cofw/index.md b/site/content/pages/datasets/cofw/index.md index 4c9f1d61..3cafe5b1 100644 --- a/site/content/pages/datasets/cofw/index.md +++ b/site/content/pages/datasets/cofw/index.md @@ -11,11 +11,11 @@ authors: Adam Harvey ------------ +## Caltech Occluded Faces in the Wild + ### sidebar ### end sidebar -## Caltech Occluded Faces in the Wild - [ PAGE UNDER DEVELOPMENT ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/duke_mtmc/index.md b/site/content/pages/datasets/duke_mtmc/index.md index 37b2cd2d..ac0a3f2e 100644 --- a/site/content/pages/datasets/duke_mtmc/index.md +++ b/site/content/pages/datasets/duke_mtmc/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## Duke MTMC + ### sidebar ### end sidebar -## Duke MTMC - [ page under development ] Duke MTMC (Multi-Target, Multi-Camera Tracking) is a dataset of video recorded on Duke University campus for research and development of networked camera surveillance systems. MTMC tracking algorithms are used for citywide dragnet surveillance systems such as those used throughout China by SenseTime[^sensetime_qz] and the oppressive monitoring of 2.5 million Uyghurs in Xinjiang by SenseNets[^sensenets_uyghurs]. In fact researchers from both SenseTime[^sensetime1] [^sensetime2] and SenseNets[^sensenets_sensetime] used the Duke MTMC dataset for their research. diff --git a/site/content/pages/datasets/feret/index.md b/site/content/pages/datasets/feret/index.md index 15e5ccf0..034ff4aa 100644 --- a/site/content/pages/datasets/feret/index.md +++ b/site/content/pages/datasets/feret/index.md @@ -11,11 +11,11 @@ authors: Adam Harvey ------------ +# FacE REcognition Dataset (FERET) + ### sidebar ### end sidebar -# FacE REcognition Dataset (FERET) - [ page under development ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/hrt_transgender/index.md b/site/content/pages/datasets/hrt_transgender/index.md index 1bca6a33..137e6dcb 100644 --- a/site/content/pages/datasets/hrt_transgender/index.md +++ b/site/content/pages/datasets/hrt_transgender/index.md @@ -14,11 +14,11 @@ authors: Adam Harvey ------------ +## HRT Transgender Dataset + ### sidebar ### end sidebar -## HRT Transgender Dataset - [ page under development ] {% include 'dashboard.html' } \ No newline at end of file diff --git a/site/content/pages/datasets/lfpw/index.md b/site/content/pages/datasets/lfpw/index.md index 48c0d82a..09506313 100644 --- a/site/content/pages/datasets/lfpw/index.md +++ b/site/content/pages/datasets/lfpw/index.md @@ -11,11 +11,11 @@ authors: Adam Harvey ------------ +## Labeled Face Parts in The Wild + ### sidebar ### end sidebar -## Labeled Face Parts in The Wild - {% include 'dashboard.html' %} -------- diff --git a/site/content/pages/datasets/lfw/index.md b/site/content/pages/datasets/lfw/index.md index bc7f3222..5d90e87f 100644 --- a/site/content/pages/datasets/lfw/index.md +++ b/site/content/pages/datasets/lfw/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## Labeled Faces in the Wild + ### sidebar ### end sidebar -## Labeled Faces in the Wild - [ PAGE UNDER DEVELOPMENT ] *Labeled Faces in The Wild* (LFW) is "a database of face photographs designed for studying the problem of unconstrained face recognition[^lfw_www]. It is used to evaluate and improve the performance of facial recognition algorithms in academic, commercial, and government research. According to BiometricUpdate.com[^lfw_pingan], LFW is "the most widely used evaluation set in the field of facial recognition, LFW attracts a few dozen teams from around the globe including Google, Facebook, Microsoft Research Asia, Baidu, Tencent, SenseTime, Face++ and Chinese University of Hong Kong." diff --git a/site/content/pages/datasets/market_1501/index.md b/site/content/pages/datasets/market_1501/index.md index 67558bef..e106a498 100644 --- a/site/content/pages/datasets/market_1501/index.md +++ b/site/content/pages/datasets/market_1501/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## Market-1501 Dataset + ### sidebar ### end sidebar -## Market-1501 Dataset - [ PAGE UNDER DEVELOPMENT] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/msceleb/index.md b/site/content/pages/datasets/msceleb/index.md index 6d45a0aa..70e85699 100644 --- a/site/content/pages/datasets/msceleb/index.md +++ b/site/content/pages/datasets/msceleb/index.md @@ -14,11 +14,11 @@ authors: Adam Harvey ------------ +## Microsoft Celeb Dataset (MS Celeb) + ### sidebar ### end sidebar -## Microsoft Celeb Dataset (MS Celeb) - [ PAGE UNDER DEVELOPMENT ] https://www.hrw.org/news/2019/01/15/letter-microsoft-face-surveillance-technology diff --git a/site/content/pages/datasets/oxford_town_centre/index.md b/site/content/pages/datasets/oxford_town_centre/index.md index c26b81e7..c32cd022 100644 --- a/site/content/pages/datasets/oxford_town_centre/index.md +++ b/site/content/pages/datasets/oxford_town_centre/index.md @@ -14,11 +14,11 @@ authors: Adam Harvey ------------ +## Oxford Town Centre + ### sidebar ### end sidebar -## Oxford Town Centre - The Oxford Town Centre dataset is a CCTV video of pedestrians in a busy downtown area in Oxford used for research and development of activity and face recognition systems.[^ben_benfold_orig] The CCTV video was obtained from a public surveillance camera at the corner of Cornmarket and Market St. in Oxford, England and includes approximately 2,200 people. Since its publication in 2009[^guiding_surveillance] the Oxford Town Centre dataset has been used in over 80 verified research projects including commercial research by Amazon, Disney, OSRAM, and Huawei; and academic research in China, Israel, Russia, Singapore, the US, and Germany among dozens more. The Oxford Town Centre dataset is unique in that it uses footage from a public surveillance camera that would otherwise be designated for public safety. The video shows that the pedestrians act normally and unrehearsed indicating they neither knew of or consented to participation in the research project. diff --git a/site/content/pages/datasets/pipa/index.md b/site/content/pages/datasets/pipa/index.md index fbf535a9..250878ff 100644 --- a/site/content/pages/datasets/pipa/index.md +++ b/site/content/pages/datasets/pipa/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## People in Photo Albums + ### sidebar ### end sidebar -## People in Photo Albums - [ PAGE UNDER DEVELOPMENT ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/pubfig/index.md b/site/content/pages/datasets/pubfig/index.md index 560e66de..5f2e1ad5 100644 --- a/site/content/pages/datasets/pubfig/index.md +++ b/site/content/pages/datasets/pubfig/index.md @@ -13,11 +13,11 @@ authors: Adam Harvey ------------ +## PubFig + ### sidebar ### end sidebar -## PubFig - [ PAGE UNDER DEVELOPMENT ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/vgg_face2/index.md b/site/content/pages/datasets/vgg_face2/index.md index d18d1c2e..acf2476e 100644 --- a/site/content/pages/datasets/vgg_face2/index.md +++ b/site/content/pages/datasets/vgg_face2/index.md @@ -10,12 +10,11 @@ authors: Adam Harvey ------------ +## VGG Face 2 ### sidebar ### end sidebar -## VGG Face 2 - [ page under development ] {% include 'dashboard.html' %} diff --git a/site/content/pages/datasets/viper/index.md b/site/content/pages/datasets/viper/index.md index e6dd167a..291b2136 100644 --- a/site/content/pages/datasets/viper/index.md +++ b/site/content/pages/datasets/viper/index.md @@ -14,11 +14,11 @@ authors: Adam Harvey ------------ +## VIPeR Dataset + ### sidebar ### end sidebar -## VIPeR Dataset - [ page under development ] *VIPeR (Viewpoint Invariant Pedestrian Recognition)* is a dataset of pedestrian images captured at University of California Santa Cruz in 2007. Accoriding to the reserachers 2 "cameras were placed in different locations in an academic setting and subjects were notified of the presence of cameras, but were not coached or instructed in any way." diff --git a/site/content/pages/datasets/youtube_celebrities/index.md b/site/content/pages/datasets/youtube_celebrities/index.md index 6ce2a347..49bfaa2e 100644 --- a/site/content/pages/datasets/youtube_celebrities/index.md +++ b/site/content/pages/datasets/youtube_celebrities/index.md @@ -10,12 +10,11 @@ authors: Adam Harvey ------------ +## YouTube Celebrities ### sidebar ### end sidebar -## YouTube Celebrities - [ page under development ] {% include 'dashboard.html' %} diff --git a/site/public/datasets/50_people_one_question/index.html b/site/public/datasets/50_people_one_question/index.html index dfd8cbff..76d22562 100644 --- a/site/public/datasets/50_people_one_question/index.html +++ b/site/public/datasets/50_people_one_question/index.html @@ -27,7 +27,8 @@
People One Question is a dataset of people from an online video series on YouTube and Vimeo used for building facial recogntion algorithms
People One Question dataset includes ... -
+

50 People 1 Question

+
Published
2013
@@ -39,8 +40,7 @@
Website
-

50 People 1 Question

-

[ page under development ]

+

[ page under development ]

Who used 50 People One Question Dataset?

diff --git a/site/public/datasets/afad/index.html b/site/public/datasets/afad/index.html index df14e7cd..832ce86a 100644 --- a/site/public/datasets/afad/index.html +++ b/site/public/datasets/afad/index.html @@ -26,7 +26,8 @@
-
+

Asian Face Age Dataset

+
Published
2017
@@ -41,8 +42,7 @@
Website
-

Asian Face Age Dataset

-

[ page under development ]

+

[ page under development ]

Who used Asian Face Age Dataset?

diff --git a/site/public/datasets/brainwash/index.html b/site/public/datasets/brainwash/index.html index 03331a2d..494856ec 100644 --- a/site/public/datasets/brainwash/index.html +++ b/site/public/datasets/brainwash/index.html @@ -27,7 +27,8 @@
Brainwash is a dataset of webcam images taken from the Brainwash Cafe in San Francisco in 2014
The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection surveillance algorithms -
+

Brainwash Dataset

+
Published
2015
@@ -48,8 +49,7 @@
Website
-

Brainwash Dataset

-

Brainwash is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 11,918 images of "everyday life of a busy downtown cafe" 1 captured at 100 second intervals throught the entire day. Brainwash dataset was captured during 3 days in 2014: October 27, November 13, and November 24. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com. 2

+

Brainwash is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 11,918 images of "everyday life of a busy downtown cafe" 1 captured at 100 second intervals throught the entire day. Brainwash dataset was captured during 3 days in 2014: October 27, November 13, and November 24. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com. 2

Brainwash is not a widely used dataset but since its publication by Stanford University in 2015, it has notably appeared in several research papers from the National University of Defense Technology in Changsha, China. In 2016 and in 2017 researchers there conducted studies on detecting people's heads in crowded scenes for the purpose of surveillance. 3 4

If you happen to have been at Brainwash cafe in San Francisco at any time on October 26, November 13, or November 24 in 2014 you are most likely included in the Brainwash dataset and have unwittingly contributed to surveillance research.

diff --git a/site/public/datasets/caltech_10k/index.html b/site/public/datasets/caltech_10k/index.html index 00b5e7fd..c7b9f894 100644 --- a/site/public/datasets/caltech_10k/index.html +++ b/site/public/datasets/caltech_10k/index.html @@ -26,7 +26,8 @@
-
+

Caltech 10K Faces Dataset

+
Published
2015
@@ -47,8 +48,7 @@
Website
-

Caltech 10K Faces Dataset

-

[ page under development ]

+

[ page under development ]

Who used Brainwash Dataset?

diff --git a/site/public/datasets/celeba/index.html b/site/public/datasets/celeba/index.html index c4caef20..e42ceb6f 100644 --- a/site/public/datasets/celeba/index.html +++ b/site/public/datasets/celeba/index.html @@ -27,7 +27,8 @@
CelebA is a dataset of people...
CelebA includes... -
+

CelebA Dataset

+
Published
2015
@@ -45,8 +46,7 @@
Website
-

CelebA Dataset

-

[ PAGE UNDER DEVELOPMENT ]

+

[ PAGE UNDER DEVELOPMENT ]

Who used CelebA Dataset?

diff --git a/site/public/datasets/cofw/index.html b/site/public/datasets/cofw/index.html index 4851e256..39e9680b 100644 --- a/site/public/datasets/cofw/index.html +++ b/site/public/datasets/cofw/index.html @@ -26,7 +26,8 @@
-
+

Caltech Occluded Faces in the Wild

+
Published
2013
@@ -38,8 +39,7 @@
Website
-

Caltech Occluded Faces in the Wild

-

[ PAGE UNDER DEVELOPMENT ]

+

[ PAGE UNDER DEVELOPMENT ]

Who used COFW Dataset?

diff --git a/site/public/datasets/duke_mtmc/index.html b/site/public/datasets/duke_mtmc/index.html index ba32484a..78067101 100644 --- a/site/public/datasets/duke_mtmc/index.html +++ b/site/public/datasets/duke_mtmc/index.html @@ -27,7 +27,8 @@
Duke MTMC is a dataset of surveillance camera footage of students on Duke University campus
Duke MTMC contains over 2 million video frames and 2,700 unique identities collected from 8 HD cameras at Duke University campus in March 2014 -
+

Duke MTMC

+
Published
2016
@@ -45,12 +46,12 @@
Website
-

Duke MTMC

+

[ page under development ]

Duke MTMC (Multi-Target, Multi-Camera Tracking) is a dataset of video recorded on Duke University campus for research and development of networked camera surveillance systems. MTMC tracking algorithms are used for citywide dragnet surveillance systems such as those used throughout China by SenseTime 1 and the oppressive monitoring of 2.5 million Uyghurs in Xinjiang by SenseNets 2. In fact researchers from both SenseTime 4 5 and SenseNets 3 used the Duke MTMC dataset for their research.

-

In this investigation into the Duke MTMC dataset, we found that researchers at Duke Univesity in Durham, North Carolina captured over 2,000 students, faculty members, and passersby into one of the most prolific public surveillance research datasets that's used around the world by commercial and defense surveillance organizations.

+

In this investigation into the Duke MTMC dataset, we found that researchers at Duke University in Durham, North Carolina captured over 2,000 students, faculty members, and passersby into one of the most prolific public surveillance research datasets that's used around the world by commercial and defense surveillance organizations.

Since it's publication in 2016, the Duke MTMC dataset has been used in over 100 studies at organizations around the world including SenseTime 4 5, SenseNets 3, IARPA and IBM 9, Chinese National University of Defense 7 8, US Department of Homeland Security 10, Tencent, Microsoft, Microsft Asia, Fraunhofer, Senstar Corp., Alibaba, Naver Labs, Google and Hewlett-Packard Labs to name only a few.

The creation and publication of the Duke MTMC dataset in 2014 (published in 2016) was originally funded by the U.S. Army Research Laboratory and the National Science Foundation 6. Though our analysis of the geographic locations of the publicly available research shows over twice as many citations by researchers from China (44% China, 20% United States). In 2018 alone, there were 70 research project citations from China.

-
A collection of 1,600 out of the 2,700 students and passersby captured into the Duke MTMC surveillance research and development dataset on . These students were also included in the Duke MTMC Re-ID dataset extension used for person re-identification. Open Data Commons Attribution License.
A collection of 1,600 out of the 2,700 students and passersby captured into the Duke MTMC surveillance research and development dataset on . These students were also included in the Duke MTMC Re-ID dataset extension used for person re-identification. Open Data Commons Attribution License.

The 8 cameras deployed on Duke's campus were specifically setup to capture students "during periods between lectures, when pedestrian traffic is heavy". 6. Camera 5 was positioned to capture students as entering and exiting the university's main chapel. Each camera's location and approximate field of view. The heat map visualization shows the locations where pedestrians were most frequently annotated in each video from the Duke MTMC datset.

+
A collection of 1,600 out of the 2,700 students and passersby captured into the Duke MTMC surveillance research and development dataset on . These students were also included in the Duke MTMC Re-ID dataset extension used for person re-identification. Open Data Commons Attribution License.
A collection of 1,600 out of the 2,700 students and passersby captured into the Duke MTMC surveillance research and development dataset on . These students were also included in the Duke MTMC Re-ID dataset extension used for person re-identification. Open Data Commons Attribution License.

The 8 cameras deployed on Duke's campus were specifically setup to capture students "during periods between lectures, when pedestrian traffic is heavy". 6. Camera 5 was positioned to capture students as entering and exiting the university's main chapel. Each camera's location and approximate field of view. The heat map visualization shows the locations where pedestrians were most frequently annotated in each video from the Duke MTMC dataset.

Duke MTMC camera locations on Duke University campus. Open Data Commons Attribution License.
Duke MTMC camera locations on Duke University campus. Open Data Commons Attribution License.
Duke MTMC camera views for 8 cameras deployed on campus © megapixels.cc
Duke MTMC camera views for 8 cameras deployed on campus © megapixels.cc
Duke MTMC pedestrian detection saliency maps for 8 cameras deployed on campus © megapixels.cc
Duke MTMC pedestrian detection saliency maps for 8 cameras deployed on campus © megapixels.cc

Who used Duke MTMC Dataset?

@@ -217,7 +218,11 @@ under Grants IIS-10-17017 and IIS-14-20894.

booktitle = {European Conference on Computer Vision workshop on Benchmarking Multi-Target Tracking}, year = {2016} } -

References

References

  • a

    https://qz.com/1248493/sensetime-the-billion-dollar-alibaba-backed-ai-company-thats-quietly-watching-everyone-in-china/

  • a

    https://foreignpolicy.com/2019/03/19/962492-orwell-china-socialcredit-surveillance/

  • ab

    "Attention-Aware Compositional Network for Person Re-identification". 2018. SemanticScholar, PDF

  • ab

    "End-to-End Deep Kronecker-Product Matching for Person Re-identification". 2018. SemanticScholar, PDF

    diff --git a/site/public/datasets/feret/index.html b/site/public/datasets/feret/index.html index 089cd351..929041df 100644 --- a/site/public/datasets/feret/index.html +++ b/site/public/datasets/feret/index.html @@ -26,7 +26,8 @@
    -
    +

    FacE REcognition Dataset (FERET)

    +
    Published
    2007
    @@ -41,10 +42,59 @@
    Website
    -

    FacE REcognition Dataset (FERET)

    -

    [ page under development ]

    -

    {% include 'dashboard.html' %}

    -

    (ignore) RESEARCH below this line

    +

    [ page under development ]

    +
    +

    Who used LFW?

    + +

    + This bar chart presents a ranking of the top countries where dataset citations originated. Mouse over individual columns to see yearly totals. These charts show at most the top 10 countries. +

    + +
    + +
    + +
    +
    + +
    +
    +
    + +
    + +

    Biometric Trade Routes

    + +

    + To help understand how LFW has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Labeled Faces in the Wild was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal research projects at that location. +

    + +
    + +
    +
    +
    + +
    +
      +
    • Academic
      • +
    • Commercial
      • +
    • Military / Government
      • +
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    + + +
    + +

    Dataset Citations

    +

    + The dataset citations used in the visualizations were collected from Semantic Scholar, a website which aggregates and indexes research papers. Each citation was geocoded using names of institutions found in the PDF front matter, or as listed on other resources. These papers have been manually verified to show that researchers downloaded and used the dataset to train or test machine learning algorithms. +

    + +
    +

    (ignore) RESEARCH below this line

    • Years: 1993-1996
    • Images: 14,126
      • @@ -63,7 +113,7 @@
      • "A release form is necessary because of the privacy laws in the United States."
      -

    Funding

    +

    Funding

    The FERET program is sponsored by the U.S. Depart- ment of Defense’s Counterdrug Technology Development Program Office. The U.S. Army Research Laboratory (ARL) is the technical agent for the FERET program. ARL designed, administered, and scored the FERET tests. George Mason University collected, processed, and main- tained the FERET database. Inquiries regarding the FERET database or test should be directed to P. Jonathon Phillips.

    diff --git a/site/public/datasets/hrt_transgender/index.html b/site/public/datasets/hrt_transgender/index.html index 231a5271..5f2229d8 100644 --- a/site/public/datasets/hrt_transgender/index.html +++ b/site/public/datasets/hrt_transgender/index.html @@ -27,7 +27,8 @@
    TBD
    TBD -
    +

    HRT Transgender Dataset

    +
    Published
    2013
    @@ -42,8 +43,7 @@
    Website
    -

    HRT Transgender Dataset

    -

    [ page under development ]

    +

    [ page under development ]

    {% include 'dashboard.html' }

    diff --git a/site/public/datasets/index.html b/site/public/datasets/index.html index b01c1ac1..75961089 100644 --- a/site/public/datasets/index.html +++ b/site/public/datasets/index.html @@ -61,6 +61,30 @@ + +
    + HRT Transgender Dataset +
    +
    2013
    +
    gender transition and facial recognition
    +
    10,564 images
    +
    38
    +
    +
    +     + + +
    + Microsoft Celeb +
    +
    2016
    +
    Large-scale face recognition
    +
    1,000,000 images
    +
    100,000
    +
    +
    +     +
    Oxford Town Centre diff --git a/site/public/datasets/lfpw/index.html b/site/public/datasets/lfpw/index.html index f734d332..c26b8583 100644 --- a/site/public/datasets/lfpw/index.html +++ b/site/public/datasets/lfpw/index.html @@ -26,7 +26,8 @@
    -
    +

    Labeled Face Parts in The Wild

    +
    Published
    2011
    @@ -35,8 +36,7 @@
    Website
     -

    Labeled Face Parts in The Wild

    -
    +

    Who used LFWP?

    diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html index 60a6bf0e..1907f959 100644 --- a/site/public/datasets/lfw/index.html +++ b/site/public/datasets/lfw/index.html @@ -27,7 +27,8 @@

    Labeled Faces in The Wild (LFW) is the first facial recognition dataset created entirely from online photos
    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. -
    +

    Labeled Faces in the Wild

    +
    Published
    2007
    @@ -42,8 +43,7 @@
    Website
     -

    Labeled Faces in the Wild

    -

    [ PAGE UNDER DEVELOPMENT ]

    +

    [ PAGE UNDER DEVELOPMENT ]

    Labeled Faces in The Wild (LFW) is "a database of face photographs designed for studying the problem of unconstrained face recognition 1. It is used to evaluate and improve the performance of facial recognition algorithms in academic, commercial, and government research. According to BiometricUpdate.com 3, 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...

    The Names and Faces dataset was the first face recognition dataset created entire from online photos. However, Names and Faces and LFW are not the first face recognition dataset created entirely "in the wild". That title belongs to the UCD dataset. Images obtained "in the wild" means using an image without explicit consent or awareness from the subject or photographer.

    diff --git a/site/public/datasets/market_1501/index.html b/site/public/datasets/market_1501/index.html index 72807efc..ad6bf458 100644 --- a/site/public/datasets/market_1501/index.html +++ b/site/public/datasets/market_1501/index.html @@ -27,7 +27,8 @@
    Market-1501 is a dataset is collection of CCTV footage from Tsinghua University
    The Market-1501 dataset includes 1,261 people from 5 HD surveillance cameras located on campus -
    +

    Market-1501 Dataset

    +
    Published
    2015
    @@ -42,8 +43,7 @@
    Website
    -

    Market-1501 Dataset

    -

    [ PAGE UNDER DEVELOPMENT]

    +

    [ PAGE UNDER DEVELOPMENT]

    Who used Market 1501?

    diff --git a/site/public/datasets/msceleb/index.html b/site/public/datasets/msceleb/index.html index be21280c..b4d02c87 100644 --- a/site/public/datasets/msceleb/index.html +++ b/site/public/datasets/msceleb/index.html @@ -27,7 +27,8 @@
    MS Celeb is a dataset of web images used for training and evaluating face recognition algorithms
    The MS Celeb dataset includes over 10,000,000 images and 93,000 identities of semi-public figures collected using the Bing search engine -
    +

    Microsoft Celeb Dataset (MS Celeb)

    +
    Published
    2016
    @@ -48,8 +49,7 @@
    Website
    -

    Microsoft Celeb Dataset (MS Celeb)

    -

    [ PAGE UNDER DEVELOPMENT ]

    +

    [ PAGE UNDER DEVELOPMENT ]

    https://www.hrw.org/news/2019/01/15/letter-microsoft-face-surveillance-technology

    https://www.scmp.com/tech/science-research/article/3005733/what-you-need-know-about-sensenets-facial-recognition-firm

    diff --git a/site/public/datasets/oxford_town_centre/index.html b/site/public/datasets/oxford_town_centre/index.html index af020855..8c95f287 100644 --- a/site/public/datasets/oxford_town_centre/index.html +++ b/site/public/datasets/oxford_town_centre/index.html @@ -27,7 +27,8 @@
    Oxford Town Centre is a dataset of surveillance camera footage from Cornmarket St Oxford, England
    The Oxford Town Centre dataset includes approximately 2,200 identities and is used for research and development of face recognition systems -
    +

    Oxford Town Centre

    +
    Published
    2009
    @@ -48,8 +49,7 @@
    Website
    -

    Oxford Town Centre

    -

    The Oxford Town Centre dataset is a CCTV video of pedestrians in a busy downtown area in Oxford used for research and development of activity and face recognition systems. 1 The CCTV video was obtained from a public surveillance camera at the corner of Cornmarket and Market St. in Oxford, England and includes approximately 2,200 people. Since its publication in 2009 2 the Oxford Town Centre dataset has been used in over 80 verified research projects including commercial research by Amazon, Disney, OSRAM, and Huawei; and academic research in China, Israel, Russia, Singapore, the US, and Germany among dozens more.

    +

    The Oxford Town Centre dataset is a CCTV video of pedestrians in a busy downtown area in Oxford used for research and development of activity and face recognition systems. 1 The CCTV video was obtained from a public surveillance camera at the corner of Cornmarket and Market St. in Oxford, England and includes approximately 2,200 people. Since its publication in 2009 2 the Oxford Town Centre dataset has been used in over 80 verified research projects including commercial research by Amazon, Disney, OSRAM, and Huawei; and academic research in China, Israel, Russia, Singapore, the US, and Germany among dozens more.

    The Oxford Town Centre dataset is unique in that it uses footage from a public surveillance camera that would otherwise be designated for public safety. The video shows that the pedestrians act normally and unrehearsed indicating they neither knew of or consented to participation in the research project.

    Who used TownCentre?

    diff --git a/site/public/datasets/pipa/index.html b/site/public/datasets/pipa/index.html index 780b3029..d02540f0 100644 --- a/site/public/datasets/pipa/index.html +++ b/site/public/datasets/pipa/index.html @@ -27,7 +27,8 @@
    People in Photo Albums (PIPA) is a dataset...
    [ add subdescrition ] -
    +

    People in Photo Albums

    +
    Published
    2015
    @@ -45,8 +46,7 @@
    Website
    -

    People in Photo Albums

    -

    [ PAGE UNDER DEVELOPMENT ]

    +

    [ PAGE UNDER DEVELOPMENT ]

    Who used PIPA Dataset?

    diff --git a/site/public/datasets/pubfig/index.html b/site/public/datasets/pubfig/index.html index 2c8bd7b1..ed593054 100644 --- a/site/public/datasets/pubfig/index.html +++ b/site/public/datasets/pubfig/index.html @@ -27,7 +27,8 @@
    PubFig is a dataset...
    [ add subdescrition ] -
    +

    PubFig

    +
    Published
    2009
    @@ -42,8 +43,7 @@
    Website
    -

    PubFig

    -

    [ PAGE UNDER DEVELOPMENT ]

    +

    [ PAGE UNDER DEVELOPMENT ]

    Who used PubFig?

    diff --git a/site/public/datasets/uccs/index.html b/site/public/datasets/uccs/index.html index 1d76de3a..27d30716 100644 --- a/site/public/datasets/uccs/index.html +++ b/site/public/datasets/uccs/index.html @@ -28,7 +28,7 @@
    UnConstrained College Students is a dataset of long-range surveillance photos of students on University of Colorado in Colorado Springs campus
    The UnConstrained College Students dataset includes 16,149 images of 1,732 students, faculty, and pedestrians and is used for developing face recognition and face detection algorithms

    UnConstrained College Students

    -
    +
    Published
    2016
    @@ -49,7 +49,7 @@
    Website
    -

    UnConstrained College Students (UCCS) is a dataset of long-range surveillance photos captured at University of Colorado Colorado Springs. According to the authors of two papers associated with the dataset, over 1,700 students and pedestrians were "photographed using a long-range high-resolution surveillance camera without their knowledge" 2. In this investigation, we examine the funding sources, contents of the dataset, photo EXIF data, and publicy available research project citations.

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    UnConstrained College Students (UCCS) is a dataset of long-range surveillance photos captured at University of Colorado Colorado Springs. According to the authors of two papers associated with the dataset, over 1,700 students and pedestrians were "photographed using a long-range high-resolution surveillance camera without their knowledge" 2. In this investigation, we examine the funding sources, contents of the dataset, photo EXIF data, and publicy available research project citations.

    According to the author's of the the UnConstrained College Students dataset it is primarliy used for research and development of "face detection and recognition research towards surveillance applications that are becoming more popular and more required nowadays, and where no automatic recognition algorithm has proven to be useful yet." Applications of this technology include usage by defense and intelligence agencies, who were also the primary funding sources of the UCCS dataset.

    In the two papers associated with the release of the UCCS dataset (Unconstrained Face Detection and Open-Set Face Recognition Challenge and Large Scale Unconstrained Open Set Face Database), the researchers disclosed their funding sources as ODNI (United States Office of Director of National Intelligence), IARPA (Intelligence Advance Research Projects Activity), ONR MURI (Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative), Army SBIR (Small Business Innovation Research), SOCOM SBIR (Special Operations Command and Small Business Innovation Research), and the National Science Foundation. Further, UCCS's VAST site explicity states they are part of the IARPA Janus, a face recognition project developed to serve the needs of national intelligence interests.

    Location on campus where students were unknowingly photographed with a telephoto lens to be used for defense and intelligence agency funded research on face recognition. Image: Google Maps
    Location on campus where students were unknowingly photographed with a telephoto lens to be used for defense and intelligence agency funded research on face recognition. Image: Google Maps

    The UCCS dataset includes the highest resolution images of any publicly available face recognition dataset discovered so far (18MP) and was, as of 2018, the "largest surveillance FR benchmark in the public domain." 3 To create the dataset, the researchers used a Canon 7D digital camera fitted with a Sigma 800mm telephoto lens and photographed students from a distance of 150–200m through their office window. Photos were taken during the morning and afternoon while students were walking to and from classes. According to an analysis of the EXIF data embedded in the photos, nearly half of the 16,149 photos were taken on Tuesdays. The most popular time was during lunch break. All of the photos were taken during the spring semester in 2012 and 2013 but the dataset was not publicy released until 2016.

    diff --git a/site/public/datasets/vgg_face2/index.html b/site/public/datasets/vgg_face2/index.html index 75d73824..3c2859a5 100644 --- a/site/public/datasets/vgg_face2/index.html +++ b/site/public/datasets/vgg_face2/index.html @@ -26,7 +26,8 @@
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    VGG Face 2

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    Published
    2015
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    Website
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    VGG Face 2

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    [ page under development ]

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    [ page under development ]

    Who used Brainwash Dataset?

    diff --git a/site/public/datasets/viper/index.html b/site/public/datasets/viper/index.html index 5b3ac35b..494c249b 100644 --- a/site/public/datasets/viper/index.html +++ b/site/public/datasets/viper/index.html @@ -27,7 +27,8 @@
    VIPeR is a person re-identification dataset of images captured at UC Santa Cruz in 2007
    VIPeR contains 1,264 images and 632 persons on the UC Santa Cruz campus and is used to train person re-identification algorithms for surveillance -
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    VIPeR Dataset

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    Published
    2007
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    Website
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    VIPeR Dataset

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    [ page under development ]

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    [ page under development ]

    VIPeR (Viewpoint Invariant Pedestrian Recognition) is a dataset of pedestrian images captured at University of California Santa Cruz in 2007. Accoriding to the reserachers 2 "cameras were placed in different locations in an academic setting and subjects were notified of the presence of cameras, but were not coached or instructed in any way."

    VIPeR is amongst the most widely used publicly available person re-identification datasets. In 2017 the VIPeR dataset was combined into a larger person re-identification created by the Chinese University of Hong Kong called PETA (PEdesTrian Attribute).

    diff --git a/site/public/datasets/youtube_celebrities/index.html b/site/public/datasets/youtube_celebrities/index.html index 39670c19..9a6ae18e 100644 --- a/site/public/datasets/youtube_celebrities/index.html +++ b/site/public/datasets/youtube_celebrities/index.html @@ -26,8 +26,8 @@
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    YouTube Celebrities

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    [ page under development ]

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    YouTube Celebrities

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    [ page under development ]

    Who used YouTube Celebrities?

    diff --git a/todo.md b/todo.md index cc4736cd..4586611e 100644 --- a/todo.md +++ b/todo.md @@ -16,7 +16,6 @@ ## Datasets - JL: this paper isn't appearing in the UCCS list of verified papers but should be included https://arxiv.org/pdf/1708.02337.pdf -- JL: add h2 dataset title above the right-sidebar so title extends full width - AH: add dataset analysis for MS Celeb, IJB-C - AH: fix dataset analysis for UCCS, brainwahs graphics - AH: add license information to each dataset page -- cgit v1.2.3-70-g09d2