Labeled Faces in the Wild aligned (LFW-a)
Yaniv Taigman and Lior Wolf and Tal Hassner

lfwa.tar.gz96.77MB
Type: Dataset
Tags:Dataset, LFW-a

Bibtex:
@article{,
title= {Labeled Faces in the Wild aligned (LFW-a)},
journal= {},
author= {Yaniv Taigman and Lior Wolf and Tal Hassner},
year= {2009},
url= {http://www.openu.ac.il/home/hassner/data/lfwa/},
abstract= {The "Labeled Faces in the Wild-a" image collection is a database of labeled, face images intended for studying Face Recognition in unconstrained images. It contains the same images available in the original Labeled Faces in the Wild data set, however, here we provide them after alignment using a commercial face alignment software. 

Some of our results, published in [1,2,3], were produced using these images. We show this alignment to improve the performance of face recognition algorithms. More information on how these images were aligned may be found in the two papers. 

We have maintained the same directory structure as in the original LFW data set, and so these images can be used as direct substitutes for those in the original image set. Note, however, that the images available here are grayscale versions of the originals.

Citation: If you find these images useful and use them in your work, please follow these guidlines:
Comply with any instructions specified for the original LFW data set
Cite one (or all) of the papers [1,2,3] below

References:

[1] Lior Wolf, Tal Hassner, and Yaniv Taigman, Effective Face Recognition by Combining Multiple Descriptors and Learned Background Statistics, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 33(10), Oct. 2011 (PDF)

[2] Lior Wolf, Tal Hassner and Yaniv Taigman, Similarity Scores based on Background Samples, Asian Conference on Computer Vision (ACCV), Xi' an, Sept 2009 (PDF)

[3] Yaniv Taigman, Lior Wolf and Tal Hassner, Multiple One-Shots for Utilizing Class Label Information, The British Machine Vision Conference (BMVC), London, Sept 2009 (project, PDF) },
keywords= {Dataset, LFW-a},
terms= {}
}

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