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.

There are now four different sets of LFW images including the original and three different types of "aligned" images. The aligned images include "funneled images" (ICCV 2007), LFW-a, which uses an unpublished method of alignment, and "deep funneled" images (NIPS 2012). Among these, LFW-a and the deep funneled images produce superior results for most face verification  algorithms over the original images and over the funneled images (ICCV 2007).

Related:
[new] Collected resources related to LFW - updated 2017/05/09.
LFW Deep Funneled Images.
LFW attributes file (see Attribute and Simile Classifiers for Face Verification, Kumar et al.).
Face Detection Data set and Benchmark (FDDB), our new database for face detection research.
Faces in Real-Life Images workshop at the European Conference on Computer Vision 2008, run by Erik Learned-Miller, Andras Ferencz, and Frederic Jurie.

Contact:

• Questions and comments can be sent to:
  Gary Huang - gbhuang@cs.umass.edu

Support:

• The building of the LFW database was supported by NSF CAREER Award number 0546666.