[1] Tolba A S, El-Baz A H, El-Harby A A A. Face Recognition: A Literature Review[J]. International Journal of Signal Processing, 2006, 2(1):88-103.
综述
[2]Hinton, G.E., Osindero, S. and Teh, Y. (2006) A Fast Learning Algorithm for Deep Belief Nets. Neural Computation, 18, 1527-1554. http://dx.doi.org/10.1162/neco.2006.18.7.1527
Hinton 2006提出的深度学习的概念
[3] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[C]// International Conference on Neural Information Processing Systems. Curran Associates Inc. 2012:1097-1105.
AlexNet的论文
[4] Chang F, Dean J, Ghemawat S, et al. Bigtable: a distributed storage system for structured data[J]. Acm Transactions on Computer Systems, 2008, 26(2):1-26.
[5] Dean J, Ghemawat S. MapReduce: simplified data processing on large clusters[M]. ACM, 2008.
[6] Ghemawat S, Gobioff H, Leung S. File and storage systems: The Google File System[J]. Acm Symposium on Operating Systems Principles Bolton Landing, 2003, 37:29-43.
Google大数据三论文
[7] Yang J, Lu W, Waibel A. Skin-Color Modeling and Adaptation[J]. Technical Report, 1997, 1352:687-694.
[8] Moghaddam B, Pentland A. Probabilistic Visual Learning for Object Representation[M]. IEEE Computer Society, 1997.
基于肤色的人脸分割方法
[9] Garcia C, Tziritas G. Face detection using quantized skin color regions merging and wavelet packet analysis[J]. IEEE Transactions on Multimedia, 2002, 1(3):264-277.
先验知识模型
[10] Yang J, Zhang D, Frangi A F, et al. Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition[J]. IEEE Trans Pattern Anal Mach Intell, 2004, 26(1):131-137.
PCA脸
[11] Goldberg P, Jerrum M. Bounding the Vapnik-Chervonenkis dimension of concept classes parameterized by real numbers[C]// Conference on Computational Learning Theory. ACM, 1993:361-369.
SVM算法，软间隔最大化
[12] Huang J, Blanz V, Heisele B. Face Recognition Using Component-Based SVM Classification and Morphable Models[C]// International Workshop on Pattern Recognition with Support Vector Machines. Springer-Verlag, 2002:334-341.
SVM与模板，识别人脸
[13] Wang X. An HOG-LBP human detector with partial occlusion handling[J]. Proc.ieee Int.conf.on Computer Vision Kyoto Japan Sept, 2009, 30(2):32-39.
HOG 人脸 ,LBP 人脸特征抽取
[14] Mita T, Kaneko T, Hori O. Joint Haar-like Features for Face Detection[C]// Tenth IEEE International Conference on Computer Vision. 2005:1619-1626.
Haar 特征，一种小波变换
[14] Drucker H, Cortes C, Jackel L D, et al. Boosting and Other Ensemble Methods[J]. Neural Computation, 1989, 6(6):1289-1301.
Yann Lecun CNN
[15] Lecun Y, Bengio Y. Convolutional networks for images, speech, and time series[M]// The handbook of brain theory and neural networks. MIT Press, 1998.
Lecun Y, Bengio Y. 于1998年提出的卷积神经网络的一些应用
[16] Hubel D H, Wiesel T N. Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex[J]. Journal of Physiology, 1962, 160(1):106-154.
卷积神经网络诞生的灵感来源，研究猫的视觉神经
[17] Lecun Y. LeNet-5, convolutional neural networks[J].
LeNet
[18] Taigman Y, Yang M, Ranzato M, et al. DeepFace: Closing the Gap to Human-Level Performance in Face Verification[C]// IEEE Conference on Computer Vision and Pattern Recognition. IEEE Computer Society, 2014:1701-1708.
deepface，经典的人脸识别论文，网上有大量该论文笔记
[19] He K, Zhang X, Ren S, et al. Deep Residual Learning for Image Recognition[J]. 2015:770-778.
ResNet ,state-of-the-art
[20] Dechter R. Learning While Searching in Constraint-Satisfaction-Problems[C]// National Conference on Artificial Intelligence. Philadelphia, Pa, August 11-15, 1986. Volume 1: Science. DBLP, 1986:178-185.
最早的深度学习概念，第一次提出的深度学习说法
[21] Viola P, Jones M. Rapid Object Detection using a Boosted Cascade of Simple Features[C]// Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on. IEEE, 2003:I-511-I-518 vol.1.
Haar 级联人脸检测方法
[22] Viola P, Jones M J. Robust Real-Time Face Detection[C]// Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on. IEEE Xplore, 2004:747.
部件人脸检测，经典论文
[23] Girshick R. Fast R-CNN[J]. Computer Science, 2015.
Fast R-CNN
[24] Ren S, He K, Girshick R, et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2015, 39(6):1137-1149.
Faster-RCNN
[25] Deep Dense Face Detector spots faces from a wide range of angles[J]. Biometric Technology Today, 2015, 2015:12.
Yahoo ,DDFD，一种人脸检测方法
[26] Zhang K, Zhang Z, Li Z, et al. Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks[J]. IEEE Signal Processing Letters, 2016, 23(10):1499-1503.
MTCNN，state-of-the-art 人脸检测方法
[27] Slice D E. Landmark coordinates aligned by procrustes analysis do not lie in Kendall’s shape space.[J]. Systematic Biology, 2001, 50(1):141-149.
普氏分析法
[28] Bertinetto L, Valmadre J, Henriques J F, et al. Fully-Convolutional Siamese Networks for Object Tracking[J]. 2016:850-865.
siamese网络
[29] Liu X, Kan M, Wanglong W U, et al. VIPLFaceNet: an open source deep face recognition SDK[J]. Frontiers of Computer Science, 2016, 11(2):208-218.
VIPL Face ,seetaFace引擎的论文
[30] Simonyan K, Zisserman A. Very Deep Convolutional Networks for Large-Scale Image Recognition[J]. Computer Science, 2014.
VGGNet的论文，LRN受到质疑
[31] Zeiler M D, Fergus R. Visualizing and Understanding Convolutional Networks[J]. 2013, 8689:818-833.
ZFNet论文，用多层连续小卷积核代替单层大卷积核
[32] Simon M, Rodner E, Denzler J. ImageNet pre-trained models with batch normalization[J]. 2016.
Batch normalization
[33] Kingma D P, Ba J. Adam: A Method for Stochastic Optimization[J]. Computer Science, 2014.
Adam 优化器
[34] Landis J R, Koch G G. An application of hierarchical kappa-type statistics in the assessment of majority agreement among multiple observers.[J]. Biometrics, 1977, 33(2):363-74.
kappa系数，用于衡量多分类的一致性
[35] Bradley A P. The use of the area under the ROC curve in the evaluation of machine learning algorithms[M]. Elsevier Science Inc. 1997.
ROC 曲线评估机器学习
[36] http://vis-www.cs.umass.edu/lfw/results.html
LFW 人脸识别排行榜，论文多多