Omkar M. Parkhi,
Andrea Vedaldi,
Andrew Zisserman
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].
Details of how to crop the face given a detection can be found in vgg_face_matconvnet package below in class faceCrop in +lib/+face_proc directory.
These models can be used for non-commercial research purposes under Creative Commons Attribution License.
Results
Downloads
- vgg_face_matconvnet.tar.gz: Face detection and VGG Face descriptor source code and models (MatConvNet)
- vgg_face_torch.tar.gz: VGG Face descriptor source code and models (Torch)
- vgg_face_caffe.tar.gz: VGG Face descriptor source code and models (Caffe)
Relevant Publications
British Machine Vision Conference, 2015
Labeled faces in the wild: A database for studying face recognition in unconstrained environments.
Technical Report 07-49, University of Massachusetts, Amherst, 2007.
Face Recognition in Unconstrained Videos with Matched Background Similarity.
Computer Vision and Pattern Recognition (CVPR), 2011.
Face detection without bells and whistles.
European Conference on Computer Vision, 2014.
Cascade Object Detection with Deformable Part Models.
Computer Vision and Pattern Recognition (CVPR), 2010.