A Survey of Deep Face Recognition

Deep face recognition greatly improves the performance of face recognition by training convolutional neural networks on large-scale data sets to obtain more robust face representation. This paper summarizes the development of depth face recognition methods. First, the existing depth face recognition methods are reviewed according to the different development stages of convolutional neural networks. Secondly, the loss functions based on Euclidean distance and angular co-sine margin are reviewed, and some task-specific face recognition methods are summarized. Then, the existing data sets and the evaluation indicators of face recognition performance are summarized, and the mainstream depth face recognition methods are compared. Finally, the current challenges and future trends of face recognition are summarized.