Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (17): 46-60.DOI: 10.3778/j.issn.1002-8331.2101-0389

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Review of Occlusion Face Recognition Methods

XU Xialing, LIU Tao, TIAN Guohui, YU Wenjuan, XIAO Dajun, LIANG Shanpeng   

  1. 1.Central China Electric Power Dispatching Control Sub-center, Central China Branch of State Grid Corporation of China, Wuhan 430077, China
    2.NARI Group Corporation(State Grid Electric Power Research Institute), Nanjing 211106, China
    3.Research and Development Technology Center, Beijing Kedong Electric Power Control System Corporation Limited, Beijing 100192, China
  • Online:2021-09-01 Published:2021-08-30



  1. 1.国家电网公司华中分部 华中电力调控分中心,武汉 430077
    2.南瑞集团(国网电力科学研究院)有限公司,南京 211106
    3.北京科东电力控制系统有限责任公司 研发技术中心,北京 100192


With the gradual expansion of the application field of face recognition, face detection in occlusion environment is facing certain technical challenges. Because of its strong learning ability, deep learning method has become a better solution to the problem of face occlusion detection, but it still faces many problems to be solved. Reducing the influence of occlusion on the performance of detection algorithm is one of the key and difficult problems in this field. This paper analyzes the related research progress from the perspective of model, algorithm and data set, compares the basic principles of different algorithms, model performance, advantages and disadvantages and existing problems, and discusses the possible research direction in the future.

Key words: face recognition, occlusion, feature, convolution neural network, countermeasure generation network, Artificial Intelligence(AI), deep learning



关键词: 人脸识别, 遮挡, 特征, 卷积神经网络, 对抗生成网络, 人工智能, 深度学习