diff options
Diffstat (limited to 'site/content/pages')
| -rw-r--r-- | site/content/pages/datasets/msceleb/index.md | 2 | ||||
| -rw-r--r-- | site/content/pages/datasets/uccs/index.md | 2 |
2 files changed, 2 insertions, 2 deletions
diff --git a/site/content/pages/datasets/msceleb/index.md b/site/content/pages/datasets/msceleb/index.md index 553cbd14..3d5c6c59 100644 --- a/site/content/pages/datasets/msceleb/index.md +++ b/site/content/pages/datasets/msceleb/index.md @@ -19,7 +19,7 @@ authors: Adam Harvey ### sidebar ### end sidebar -Microsoft Celeb (MS Celeb) is a dataset of 10 million face images scraped from the internet and used for research and development of large-scale biometric recognition systems. According to Microsoft Research, who created and published the [dataset](https://www.microsoft.com/en-us/research/publication/ms-celeb-1m-dataset-benchmark-large-scale-face-recognition-2/) in 2016, MS Celeb is the largest publicly available face recognition dataset in the world, containing over 10 million images of nearly 100,000 individuals. Microsoft's goal in building this dataset was to distribute an initial training dataset of 100,000 individuals' images, and to use this dataset to accelerate research into recognizing a larger target list of one million people "using all the possibly collected face images of this individual on the web as training data".[^msceleb_orig] +Microsoft Celeb (MS Celeb) is a dataset of 10 million face images scraped from the Internet and used for research and development of large-scale biometric recognition systems. According to Microsoft Research, who created and published the [dataset](https://www.microsoft.com/en-us/research/publication/ms-celeb-1m-dataset-benchmark-large-scale-face-recognition-2/) in 2016, MS Celeb is the largest publicly available face recognition dataset in the world, containing over 10 million images of nearly 100,000 individuals. Microsoft's goal in building this dataset was to distribute an initial training dataset of 100,000 individuals' images, and to use this dataset to accelerate research into recognizing a larger target list of one million people "using all the possibly collected face images of this individual on the web as training data".[^msceleb_orig] These one million people, defined by Microsoft Research as "celebrities", are often merely people who must maintain an online presence for their professional lives. Microsoft's list of 1 million people is an expansive exploitation of the current reality that for many people, including academics, policy makers, writers, artists, and especially journalists, maintaining an online presence is mandatory. This fact should not allow Microsoft or anyone else to use their biometrics for research and development of surveillance technology. Many names in the target list even include people critical of the very technology Microsoft is using their name and biometric information to build. The list includes digital rights activists like Jillian York; artists critical of surveillance including Trevor Paglen, Jill Magid, and Aram Bartholl; Intercept founders Laura Poitras, Jeremy Scahill, and Glenn Greenwald; Data and Society founder danah boyd; and even Julie Brill, the former FTC commissioner responsible for protecting consumer privacy, to name a few. diff --git a/site/content/pages/datasets/uccs/index.md b/site/content/pages/datasets/uccs/index.md index d37db132..0850bd99 100644 --- a/site/content/pages/datasets/uccs/index.md +++ b/site/content/pages/datasets/uccs/index.md @@ -44,7 +44,7 @@ The two research papers associated with the release of the UCCS dataset ([Uncons In 2017, one year after its public release, the UCCS face dataset formed the basis for a defense and intelligence agency funded [face recognition challenge](http://www.face-recognition-challenge.com/) project 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](https://erodner.github.io/ial2018eccv/) at the European Computer Vision Conference (ECCV) in Munich, Germany. -As of April 15, 2019, the UCCS dataset is no longer available for public download. But during the three years it was publicly available (2016-2019) the UCCS dataset appeared in at least 6 publicly available research papers including verified usage from Beihang University who is known to provide research and development for China's military; and Vision Semantics Ltd who lists the UK Ministory of Defence as a project partner. +As of April 15, 2019, the UCCS dataset is no longer available for public download. But during the three years it was publicly available (2016-2019) the UCCS dataset appeared in at least 6 publicly available research papers including verified usage from Beihang University who is known to provide research and development for China's military; and Vision Semantics Ltd who lists the UK Ministry of Defence as a project partner. {% include 'dashboard.html' %} |