Overview
This page contains the download links for the source code for computing the VGG-Face CNN descriptor, described in [1].
The VGG-Face CNN descriptors are computed using our CNN implementation based on the VGG-Very-Deep-16 CNN architecture as described in [1] and are evaluated on the Labeled Faces in the Wild [2] and the YouTube Faces [3] dataset.
Additionally the code also contains our fast implementation of the DPM Face detector of [3] using the cascade DPM code of [4].
Results
Downloads
Relevant Publications
[1] O. M. Parkhi, A. Vedaldi, A. Zisserman
British Machine Vision Conference, 2015
@InProceedings{Parkhi15, author = "Parkhi, O. M. and Vedaldi, A. and Zisserman, A.", title = "Deep Face Recognition", booktitle = "British Machine Vision Conference", year = "2015", } [2] G. B. Huang, M. Ramesh, T. Berg, E. Learned-Miller
Labeled faces in the wild: A database for studying face recognition in unconstrained environments.
Technical Report 07-49, University of Massachusetts, Amherst, 2007.
[3] L. Wolf, T. Hassner, I. Maoz
Face Recognition in Unconstrained Videos with Matched Background Similarity.
Computer Vision and Pattern Recognition (CVPR), 2011.
[4] M. Mathias, R. Benenson, M. Pedersoli, L. Van Gool
Face detection without bells and whistles.
European Conference on Computer Vision, 2014.
[5] P. Felzenszwalb, R. Girshick, D. McAllester
Cascade Object Detection with Deformable Part Models.
Computer Vision and Pattern Recognition (CVPR), 2010.