参考文献
［1]A survey on techniques to handle face recognition challenges: occlusion，single sample per subject and expression［J]. Artificial Intelligence Review，2019， （52）: 949-979.
［2]Wang M， Deng W H. Deep Face Recognition: A Survey［J]. arXiv， 2018:1804.06655.
［3]Guo G， Zhang N. A survey on deep learning based face recognition［J].Computer Vision and Image Understanding， 2019， （189）.
［4]走近深度学习人脸识别［EB/OL]. 2020-03-01. https://www.sohu.com/a/227266768_500659.
［5]人脸识别方向系列论文［EB/OL]. 2020-03-01. https://blog.csdn.net/ code_mart/article/details/100120799.
［6]人脸识别网络模型、损失函数、数据集相关总结［EB/OL]. 2020-03-01.https://www.jianshu.com/p/e57205edc364.
［7]Sun Y， Wang X G， Tang X O. Deep Learning Face Representation from Predicting 10000Classes［C]. CVPR 2014， 2014: 1891-1898.
［8]Sun Y， Wang X G， Tang X O. Deeply Learned Face Representations are Sparse， Selective， and Robust［C]. CVPR 2015， 2015: 2892-2900.
［9]DeepID 1， DeepID 2［EB/OL]. 2020-03-01. https://www.cnblogs.com/venus024/p/5632243.html.
［10]DeepID 1， DeepID 2， DeepID 2+， DeepID 3［EB/OL]. 2020-03-01. https://blog.csdn. net/yuanchhene ducn/article/ details/51034463.
［11]Implementation of DeepID 1using tensorflow［EB/OL]. 2020-03-01. https://github. com/jinze1994/ DeepID 1.
［12]Practise of DeepID for Face Classification［EB/OL]. 2020-03-01. https://github.com/ stdcoutzyx/ DeepID_ FaceClassify.
［13]Schroff F， Kalenichenko D， Philbin J. FaceNet: A unified embedding for face recognition and clustering［C]. CVPR 2015， 2015: 815-823.
［14]人脸识别-FaceNet［EB/OL]. 2020-03-01. https://blog.csdn.net/baidu_27643275/article/details/79222206.
［15]FaceNet 官方源代码［EB/OL]. 2020-03-01. https://github.com/davidsandberg/facenet.
［16]Siamese（孪生）网络［EB/OL]. 2020-03-01. https://blog.csdn.net/qq_15192373/article/details/78404761.
［17]Zagoruyko S， Komodakis N. Learning to Compare Image Patches Via Convolutional Neural Nnetworks［C]. CVPR 2015， 2015: 4353-4361.
［18]Siamese network 孪生神经网络——一个简单神奇的结构［EB/OL]. 2020-03-01.https://www. jianshu. com/p/92d7f6eaacf5.
［19]Siamese and triplet networks with online pair/triplet mining in PyTorch［EB/OL].2020-03-01.https://github.com/adambielski/siamese-triplet.
［20]Deng J K， Guo J， Xue N N， et al. ArcFace: Additive Angular Margin Loss for Deep Face Recognition［C]. CVPR 2019， 2019: 4690-4699.
［21]A-Softmax 的总结及与L-Softmax 的对比［EB/OL]. 2020-03-01. https://www.cnblogs.com/heguanyou/p/7503025.html.
［22]度量学习中损失函数的学习与深入理解［EB/OL]. 2020-03-01. https://www.icode9.com/content-4-252842.html.
［23]ArcFace 算法笔记［EB/OL]. 2020-03-01. https://blog.csdn.net/u014380165/article/details/80645489.
［24]ArcFace 解析［EB/OL]. 2020-03-01. https://zhuanlan.zhihu.com/p/76541084.
［25]人脸识别：《Arcface》论文详解［EB/OL]. 2020-03-01. https://blog.csdn.net/shentanyue/article/details/82109580.
［26]ArcFace 与人脸识别三要素［EB/OL]. 2020-03-01. https://blog.csdn.net/yiran103/article/details/83684613.
［27]Pytorch0.4.1codes for InsightFace［EB/OL]. 2020-03-01. https://github.com/TreB1eN/InsightFace_Pytorch.
［28]SphereFace， CosFace， ArcFace［EB/OL]. 2020-03-01. https://louishsu.xyz/2019/07/13/SphereFace-CosFace-ArcFace/.
［29]论文阅读之ArcFace［EB/OL]. 2020-03-01. https://blog.csdn.net/Wuzebiao2016/article/details/81839452.
［30]深度人脸识别综述［EB/OL]. 2020-03-01. https://www.cnblogs.com/CSLaker/p/10537749.html.