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

Abstract:

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