A Survey of Face Recognition
It serves as a tutorial material for practical face recognition technology in industry, targeting researchers and practitioners, but is incremental as it compiles existing knowledge.
This survey paper provides an introduction to face recognition, covering its history, algorithms, datasets, and applications, and includes experimental analysis on backbone size and data distribution effects.
Recent years witnessed the breakthrough of face recognition with deep convolutional neural networks. Dozens of papers in the field of FR are published every year. Some of them were applied in the industrial community and played an important role in human life such as device unlock, mobile payment, and so on. This paper provides an introduction to face recognition, including its history, pipeline, algorithms based on conventional manually designed features or deep learning, mainstream training, evaluation datasets, and related applications. We have analyzed and compared state-of-the-art works as many as possible, and also carefully designed a set of experiments to find the effect of backbone size and data distribution. This survey is a material of the tutorial named The Practical Face Recognition Technology in the Industrial World in the FG2023.