From 8165ba984432ec0b00f6f23cdf09fc90f450993e Mon Sep 17 00:00:00 2001 From: adamhrv Date: Sat, 2 Mar 2019 13:25:47 +0100 Subject: css tweaks, brainwash --- site/public/about/index.html | 13 ++++++++++--- site/public/about/terms/index.html | 1 + site/public/datasets/lfw/index.html | 2 +- site/public/datasets/vgg_face2/index.html | 19 +++++++++++++++++++ 4 files changed, 31 insertions(+), 4 deletions(-) (limited to 'site/public') diff --git a/site/public/about/index.html b/site/public/about/index.html index 71038691..e2ce409d 100644 --- a/site/public/about/index.html +++ b/site/public/about/index.html @@ -31,13 +31,20 @@ -

Project Statistics

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Project Started
2012
Datasets Discovered
325
Analyzed So Far
10

Credits

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Author
Adam Harvey
Development
Jules LaPlace
Research Assistance
Berit Gilma
Supported by
Mozilla

MegaPixels is an art and research project about the origins and ethics of facial analysis datasets. Where do they come from? Who's included? Who created it and for what reason?

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Recent Press

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MegaPixels is an art and research project by Adam Harvey about the origins and ethics of facial analysis datasets. Where do they come from? Who's included? Who created it and for what reason?

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MegaPixels sets out to answer to these questions and reveal the stories behind the millions of images used to train, evaluate, and power the facial recognition surveillance algorithms used today. MegaPixels is authored by Adam Harvey, developed in collaboration with Jules LaPlace, and produced in partnership with Mozilla.

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MegaPixels sets out to answer to these questions and reveal the stories behind the millions of images used to train, evaluate, and power the facial recognition surveillance algorithms used today. MegaPixels is authored by Adam Harvey, developed in collaboration with Jules LaPlace, and produced in partnership with Mozilla.

MegaPixels sets out to answer to these questions and reveal the stories behind the millions of images used to train, evaluate, and power the facial recognition surveillance algorithms used today. MegaPixels is authored by Adam Harvey, developed in collaboration with Jules LaPlace, and produced in partnership with Mozilla.

Adam Harvey

Adam Harvey is an American artist and researcher based in Berlin. 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 is currently a researcher in residence at Karlsruhe HfG studying artifical intelligence and datasets.

Jules LaPlace

Jules LaPlace is an American artist and technologist also based in Berlin. He was previously the CTO of a NYC digital agency and currently works at VFRAME, developing computer vision for human rights groups, and building creative software for artists.

diff --git a/site/public/about/terms/index.html b/site/public/about/terms/index.html index 76cf1159..c90f1c9d 100644 --- a/site/public/about/terms/index.html +++ b/site/public/about/terms/index.html @@ -32,6 +32,7 @@
  • About
  • Press
  • Credits
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  • Research Methodology
  • Disclaimer
  • Terms and Conditions
  • Privacy Policy
    • diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html index a8a0aa4b..9657b866 100644 --- a/site/public/datasets/lfw/index.html +++ b/site/public/datasets/lfw/index.html @@ -43,7 +43,7 @@

    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.

    Biometric Trade Routes

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    To understand how this dataset has been used, its citations have been geocoded to show an approximate geographic digital trade route of the biometric data. Lines indicate an organization (education, commercial, or governmental) that has cited the LFW dataset in their research. Data is compiled from Semantic Scholar.

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    [convert to template] To understand how this dataset has been used, its citations have been geocoded to show an approximate geographic digital trade route of the biometric data. Lines indicate an organization (education, commercial, or governmental) that has cited the LFW dataset in their research. Data is compiled from Semantic Scholar.

    Synthetic Faces

    To visualize the types of photos in the dataset without explicitly publishing individual's identities a generative adversarial network (GAN) was trained on the entire dataset. The images in this video show a neural network learning the visual latent space and then interpolating between archetypical identities within the LFW dataset.

    Synthetically generated face from the visual space of LFW dataset
    Synthetically generated face from the visual space of LFW dataset
    diff --git a/site/public/datasets/vgg_face2/index.html b/site/public/datasets/vgg_face2/index.html index f06bc879..d0a161cb 100644 --- a/site/public/datasets/vgg_face2/index.html +++ b/site/public/datasets/vgg_face2/index.html @@ -32,6 +32,25 @@ +

    Names and descriptions

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    TODO

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