Labeled Faces in the Wild - aligned with deep funneling
Gary B. Huang and Marwan Mattar and Honglak Lee and Erik Learned-Miller

lfw-deepfunneled.tgz 108.76MB
Type: Dataset

Metadata:
@article{,
title= {Labeled Faces in the Wild - aligned with deep funneling},
journal= {},
author= {Gary B. Huang and Marwan Mattar and Honglak Lee and Erik Learned-Miller},
booktitle= {NIPS},
year= {2012},
url= {http://vis-www.cs.umass.edu/lfw/},
abstract= {Data from the paper:
Learning to Align from Scratch
Gary B. Huang and Marwan Mattar and Honglak Lee and Erik Learned-Miller
NIPS 2012

Welcome to Labeled Faces in the Wild, a database of face photographs designed for studying the problem of unconstrained face recognition. The data set contains more than 13,000 images of faces collected from the web. Each face has been labeled with the name of the person pictured. 1680 of the people pictured have two or more distinct photos in the data set. The only constraint on these faces is that they were detected by the Viola-Jones face detector. More details can be found in the technical report below.

Information:
13233 images
5749 people
1680 people with two or more images},
keywords= {Dataset, umass, lfw, faces},
terms= {}
}

Citation:
Huang, G. B., Mattar, M., Lee, H., & Learned-Miller, E.. (2012). Labeled Faces in the Wild - aligned with deep funneling [Data set]. Academic Torrents. https://academictorrents.com/details/692d556e6f2fcb430adeffc464eb8b0a6da58f65

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