Abstract: Compared with iris, fingerprint, gait, and other biometric recognition technologies, face recognition has attracted wide attention from academia to industry due to its unique advantages such as natural, convenient, and user-friendly experience. In recent years, driven by deep learning technology, face recognition has made a breakthrough, which shows strong robustness even when suffering from obstacles like facial expression, head pose, illumination, and external occlusions. In particular, deep face recognition technologies have been widely used in security, finance, education, transportation, new retail, and other applications. We realise that in the process of deep face recognition technology becoming widespread, there is an urgent need for some review articles to summarise the basic principles and methods of deep face recognition. This paper first briefly reviews the development of face recognition and then introduces the deep learning based face recognition methods from five aspects: face preprocessing, deep feature learning, feature comparison, face datasets, and evaluation. Finally, the development trend of deep face recognition is discussed.

Key words: face recognition, deep learning, convolutional neural network, feature learning