From b3bfb2f6f34f5065658e4c0ef289791ab24e5ae2 Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Tue, 16 Apr 2019 17:24:25 +0200 Subject: wide sidebar --- site/public/datasets/lfw/index.html | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'site/public/datasets/lfw/index.html') 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. -
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+ HRT Transgender Dataset +
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2013
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gender transition and facial recognition
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10,564 images
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38
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+ Microsoft Celeb +
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2016
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Large-scale face recognition
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1,000,000 images
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100,000
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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 @@

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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

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Market-1501 Dataset

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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)

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Microsoft Celeb Dataset (MS Celeb)

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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

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Oxford Town Centre

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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.

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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...
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People in Photo Albums

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People in Photo Albums

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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...
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PubFig

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PubFig

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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

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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.

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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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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 -

VIPeR Dataset

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VIPeR Dataset

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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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YouTube Celebrities

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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