Dlib offers a high-quality face recognition algorithm based on deep learning. Dlib implements a face recognition algorithm that offers state-of-the-art accuracy. More specifically, the model has an accuracy of 99.38% on the labeled faces in the wild database.
The implementation of this algorithm is based on the ResNet-34 network proposed in the paper Deep Residual Learning for Image Recognition (2016), which was trained using three million faces. The created model (21.4 MB) can be downloaded from https://github.com/davisking/dlib-models/blob/master/dlib_face_recognition_resnet_model_v1.dat.bz2.
This network is trained in a way that generates a 128-dimensional (128D) descriptor, used to quantify the face. The training ...
