From 406d857c61fb128a48281a52899ddf77b68201be Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Thu, 28 Feb 2019 18:32:39 +0100 Subject: threejs splash page on the index --- site/public/datasets/index.html | 2 +- site/public/index.html | 166 +++------------------------------------- site/public/info/index.html | 2 +- 3 files changed, 12 insertions(+), 158 deletions(-) (limited to 'site/public') diff --git a/site/public/datasets/index.html b/site/public/datasets/index.html index 17c938ac..7398da17 100644 --- a/site/public/datasets/index.html +++ b/site/public/datasets/index.html @@ -29,7 +29,7 @@

Facial Recognition Datasets

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Found
275 datasets
Created between
1993-2018
Smallest dataset
20 images
Largest dataset
10,000,000 images
Highest resolution faces
450x500 (Unconstrained College Students)
Lowest resolution faces
16x20 pixels (QMUL SurvFace)

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MegaPixels
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- MegaPixels is an art project that explores the dark side of face recognition datasets and the future of computer vision. -
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- Made by Adam Harvey in collaboration with Jules Laplace, and in partnership with Mozilla.
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Face Recognition Datasets

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- MegaPixels is an online art project that explores the history of face recognition from the perspective of datasets. MegaPixels aims to unravel the meanings behind the data and expose the darker corners of the biometric industry that have contributed to its growth. -

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- Through a mix of case studies, visualizations, and interactive tools, Megapixels will use face recognition datasets to tell the history of modern biometrics. Many people have contributed to the development of face recignition technology, both wittingly and unwittingly. Not only scientists, but also celebrities and regular internet users have played a part. -

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- Face recognition is a mess of contradictinos. It works, yet it doesn't actually work. It's cheap and accessible, but also expensive and out of control. Face recognition research has achieved headline grabbing superhuman accuracies over 99.9%, yet in practice it's also dangerously inaccurate. -

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- During a trial installation at Sudkreuz station in Berlin in 2018, 20% of the matches were wrong, a number so low that it should not have any connection to law enforcement or justice. And in London, the Metropolitan police had been using face recognition software that mistakenly identified an alarming 98% of people as criminals, which perhaps is a crime itself. -

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Dataset Portraits

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- We have prepared detailed case studies of some of the more noteworthy datasets, including tools to help you learn what is contained in these datasets, and even whether your own face has been used to train these algorithms. -

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Face Analysis

Results are only stored for the duration of the analysis and are deleted when you leave this page.

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