libfaceid is a research framework for prototyping of face recognition solutions. It seamlessly integrates multiple detection, recognition and liveness models w/ speech synthesis and speech recognition.
C++ project to implement MTCNN, a perfect face detect algorithm, on different DL frameworks. The most popular frameworks: caffe/mxnet/tensorflow, are all suppported now
A PyTorch implementation of Google's FaceNet [1] paper for training a facial recognition model with Triplet Loss and an implementation of the Shenzhen Institutes of Advanced Technology's 'Center Loss' [2] combined with Cross Entropy Loss using the VGGFace2 dataset. A pre-trained model using Triplet Loss is available for download.
A small-scale flask server facial recognition system, using a pre-trained facenet model with real-time web camera face recognition functionality, and a pre-trained Multi-Task Cascading Convolutional Neural Network (MTCNN) for face detection and cropping.