A survey on deep learning based face recognition

Deep learning, in particular the deep convolutional neural networks, has received increasing interests in face recognition recently, and a number of deep learning methods have been proposed. This paper summarizes about 330 contributions in this area. It reviews major deep learning concepts pertinent...

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Vydáno v:Computer vision and image understanding Ročník 189; s. 102805
Hlavní autoři: Guo, Guodong, Zhang, Na
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 01.12.2019
Témata:
Artificial Neural Network
Autoencoder
Convolutional Neural Networks
Deep learning
Face recognition
Generative Adversarial Networks
Deep learning
Face recognition
Artificial Neural Network
Autoencoder
41A10
65D05
65D17
Generative Adversarial Networks
Convolutional Neural Networks
41A05
ISSN:1077-3142, 1090-235X
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Popis
Shrnutí:Deep learning, in particular the deep convolutional neural networks, has received increasing interests in face recognition recently, and a number of deep learning methods have been proposed. This paper summarizes about 330 contributions in this area. It reviews major deep learning concepts pertinent to face image analysis and face recognition, and provides a concise overview of studies on specific face recognition problems, such as handling variations in pose, age, illumination, expression, and heterogeneous face matching. A summary of databases used for deep face recognition is given as well. Finally, some open challenges and directions are discussed for future research. [Display omitted] •Presents a comprehensive survey of deep learning based face recognition methods.•Categorizes various approaches systematically.•Focuses on architectures, loss functions and other related things.•Includes specific issues on pose, expression, 3D, heterogeneous matching, etc.•Contains a broad review of related face databases.
ISSN:1077-3142
1090-235X
DOI:10.1016/j.cviu.2019.102805