【导读】@polarisZhao同学将众多人脸相关资源进行了汇总,让你从入门到精通。
github链接:
https://github.com/timzhang642/3D-Machine-Learning
作者:@polarisZhao
【论文/算法】
人脸识别
Deep ID Series
DeepID1: Deep Learning Face Representation from Predicting 10,000 Classes [Yi Sun et al., 2014]
DeepID2: Deep Learning Face Representation by Joint Identification-Verification [Yi Sun et al., 2014]
DeepID2+: Deeply learned face representations are sparse, selective, and robust [Yi Sun et al., 2014]
DeepIDv3: DeepID3: Face Recognition with Very Deep Neural Networks [Yi Sun et al., 2015]
FaceNet: [third-party implemention]
FaceNet: A Unified Embedding for Face Recognition and Clustering [Florian Schroff et al., 2015]
Deep Face:
Deep Face Recognition [Omkar M. Parkhi et al., 2015]
2. margin based classification
Center Loss: [code] A Discriminative Feature Learning Approach for Deep Face Recognition [Yandong Wen et al., 2016]
Large-Margin Softmax Loss [code] Large-Margin Softmax Loss for Convolutional Neural Networks(L-Softmax loss)[Weiyang Liu al., 2017]
SphereFace: A-Softmax [code] SphereFace: Deep Hypersphere Embedding for Face Recognition [Weiyang Liu al., 2017]
NormFace [code]
NormFace: L2 Hypersphere Embedding for Face Verification [Feng Wang al., 2017]
COCO Loss: [code]
Rethinking Feature Discrimination and Polymerization for Large-scale Recognition [Yu Liu al., 2017]
AM-Softmax [code] AM : Additive Margin Softmax for Face Verification [Feng Wang al., 2018]
CosFace:
CosFace: Large Margin Cosine Loss for Deep Face Recognition(Tencent AI Lab) [Hao Wang al., 2018]
ArcFace: [code]
ArcFace: Additive Angular Margin Loss for Deep Face Recognition [Jiankang Deng al., 2018]
CCL:
Face Recognition via Centralized Coordinate Learning [Xianbiao al., 2018]
3. 3D face recognition
Deep 3D Face Identification [Donghyun Kim al., 2017]
Learning from Millions of 3D Scans for Large-scale 3D Face Recognition[Syed Zulqarnain al., 2018]
4. others
Beyond triplet loss: a deep quadruplet network for person re-identification[Weihua Chen al., 2017]
Range Loss for Deep Face Recognition with Long-tail [Xiao Zhang al., 2016]
Feature Incay for Representation Regularization[Yuhui Yuan al., 2017]
人脸检测
Cascade [code]
A Convolutional Neural Network Cascade for Face Detection[Haoxiang Li al., 2015]
MTCNN [code]
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks[K. Zhang al., 2016]
Face R-CNN
Face R-CNN[H. Wang, Z. Li, X. Ji, Y. Wang. et.al 2017]
SSH [code]
SSH: Single Stage Headless Face Detector[M. Najibi, al., 2017 ]
HR [code]
Finding Tiny Faces [Peiyun Hu, Deva Ramanan, 2017]
FaceBoxes code**
Faceboxes: A CPU Real-time Face Detector with High Accuracy[Zhang, Shifeng al., 2017]
PyramidBox
PyramidBox: A Context-assisted Single Shot Face Detector[Xu Tang al., 2018]
人脸对齐
Look at Boundary: A Boundary-Aware Face Alignment Algorithm[Wayne Wu al., 2018]
PFLD: A Practical Facial Landmark Detector[Xiaojie Guo al., 2019]
其他
Exploring Disentangled Feature Representation Beyond Face Identification[Yu Liu al., 2018]
【开源库】
【数据集】
人脸识别
2D人脸识别
视频人脸识别
3D人脸识别
Anti-Spoofing
跨年龄、跨姿态
人脸检测
人脸特征
其他
【会议/期刊】
会议
ICCV: IEEE International Conference on Computer Vision
CVPR: IEEE Conference on Computer Vision and Pattern Recognition
ECCV: European Conference on Computer Vision
FG: IEEE International Conference on Automatic Face and Gesture Recognition
BMVC: The British Machine Vision Conference
biometrics:
IJCB[ICB+BTAS]:International Joint Conference on Biometrics
ICB: International Conference on Biometrics
BTAS: IEEE International Conference on Biometrics: Theory, Applications and Systems
Workshop
AMFG: IEEE workshop on Analysis and Modeling of Faces and Gestures
CVPR Workshop on Biometrics、
期刊
TPAMI: IEEE Transactions on Pattern Analysis and Machine Intelligence
IJCV: International Journal of Computer Vision
TIP: IEEE Transactions on Image Processing
TIFS: [IEEE Transactions on Information Forensics and Security](IEEE Transactions on Information Forensics and Security)
PR: Pattern Recognition
专 · 知
专知《深度学习:算法到实战》课程全部完成!510+位同学在学习,现在报名,限时优惠!网易云课堂人工智能畅销榜首位!
欢迎微信扫一扫加入专知人工智能知识星球群,获取最新AI专业干货知识教程视频资料和与专家交流咨询!
请加专知小助手微信(扫一扫如下二维码添加),加入专知人工智能主题群,咨询《深度学习:算法到实战》课程,咨询技术商务合作~
请PC登录www.zhuanzhi.ai或者点击阅读原文,注册登录专知,获取更多AI知识资料!
点击“阅读原文”,了解报名专知《深度学习:算法到实战》课程