├── LICENSE ├── README.md ├── css └── extra.css ├── docs ├── about.md ├── data │ ├── highlight_face_alignment.jpg │ ├── highlight_face_detection.jpg │ ├── highlight_face_recognation.jpg │ └── lffd_v2_gpu_result.gif ├── face_3d.md ├── face_action.md ├── face_adversarial-attack.md ├── face_anti-spoofing.md ├── face_benchmark-and-dataset.md ├── face_capture.md ├── face_clustering.md ├── face_cross-modal.md ├── face_detection.md ├── face_expression.md ├── face_gan.md ├── face_landmark.md ├── face_lib-and-tool.md ├── face_manipulation.md ├── face_recognition.md └── index.md ├── js ├── baidu-tongji.js └── extra.js ├── mkdocs-material.yml ├── mkdocs-readthedocs.yml ├── mkdocs.yml └── site ├── 404.html ├── about └── index.html ├── assets ├── fonts │ ├── font-awesome.css │ ├── material-icons.css │ └── specimen │ │ ├── FontAwesome.ttf │ │ ├── FontAwesome.woff │ │ ├── FontAwesome.woff2 │ │ ├── MaterialIcons-Regular.ttf │ │ ├── MaterialIcons-Regular.woff │ │ └── MaterialIcons-Regular.woff2 ├── images │ ├── favicon.png │ └── icons │ │ ├── bitbucket.1b09e088.svg │ │ ├── github.f0b8504a.svg │ │ └── gitlab.6dd19c00.svg ├── javascripts │ ├── application.245445c6.js │ ├── lunr │ │ ├── lunr.da.js │ │ ├── lunr.de.js │ │ ├── lunr.du.js │ │ ├── lunr.es.js │ │ ├── lunr.fi.js │ │ ├── lunr.fr.js │ │ ├── lunr.hu.js │ │ ├── lunr.it.js │ │ ├── lunr.ja.js │ │ ├── lunr.jp.js │ │ ├── lunr.multi.js │ │ ├── lunr.nl.js │ │ ├── lunr.no.js │ │ ├── lunr.pt.js │ │ ├── lunr.ro.js │ │ ├── lunr.ru.js │ │ ├── lunr.stemmer.support.js │ │ ├── lunr.sv.js │ │ ├── lunr.th.js │ │ ├── lunr.tr.js │ │ ├── tinyseg.js │ │ └── wordcut.js │ └── modernizr.74668098.js └── stylesheets │ ├── application-palette.01803549.css │ └── application.0284f74d.css ├── data └── lffd_v2_gpu_result.gif ├── face_3d └── index.html ├── face_action └── index.html ├── face_adversarial-attack └── index.html ├── face_anti-spoofing └── index.html ├── face_benchmark-and-dataset └── index.html ├── face_capture └── index.html ├── face_clustering └── index.html ├── face_cross-modal └── index.html ├── face_detection └── index.html ├── face_expression └── index.html ├── face_gan └── index.html ├── face_landmark └── index.html ├── face_lib-and-tool └── index.html ├── face_manipulation └── index.html ├── face_recognition └── index.html ├── index.html ├── search └── search_index.json ├── sitemap.xml └── sitemap.xml.gz /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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**2DASL**: Joint 3D Face Reconstruction and Dense Face Alignment from A Single Image with 2D-Assisted Self-Supervised Learning [[paper]](https://arxiv.org/abs/1903.09359 "arXiv2019") [[code]](https://github.com/XgTu/2DASL "PyTorch & Matlab") 3 | - **MVF-Net**: Multi-View 3D Face Morphable Model Regression [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Wu_MVF-Net_Multi-View_3D_Face_Morphable_Model_Regression_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/Fanziapril/mvfnet "PyTorch") 4 | - Dense 3D Face Decoding Over 2500FPS: Joint Texture & Shape Convolutional Mesh Decoders [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhou_Dense_3D_Face_Decoding_Over_2500FPS_Joint_Texture__Shape_CVPR_2019_paper.pdf "CVPR2019") 5 | - Towards High-Fidelity Nonlinear 3D Face Morphable Model [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Tran_Towards_High-Fidelity_Nonlinear_3D_Face_Morphable_Model_CVPR_2019_paper.pdf "CVPR2019") [[project]](http://cvlab.cse.msu.edu/project-nonlinear-3dmm.html) 6 | - Combining 3D Morphable Models: A Large Scale Face-And-Head Model [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Ploumpis_Combining_3D_Morphable_Models_A_Large_Scale_Face-And-Head_Model_CVPR_2019_paper.pdf "CVPR2019") 7 | - Disentangled Representation Learning for 3D Face Shape [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Jiang_Disentangled_Representation_Learning_for_3D_Face_Shape_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/zihangJiang/DR-Learning-for-3D-Face "Keras") 8 | - Self-Supervised Adaptation of High-Fidelity Face Models for Monocular Performance Tracking [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yoon_Self-Supervised_Adaptation_of_High-Fidelity_Face_Models_for_Monocular_Performance_Tracking_CVPR_2019_paper.pdf "CVPR2019") 9 | - **MMFace**: A Multi-Metric Regression Network for Unconstrained Face Reconstruction [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yi_MMFace_A_Multi-Metric_Regression_Network_for_Unconstrained_Face_Reconstruction_CVPR_2019_paper.pdf "CVPR2019") 10 | - **RingNet**: Learning to Regress 3D Face Shape and Expression From an Image Without 3D Supervision [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Sanyal_Learning_to_Regress_3D_Face_Shape_and_Expression_From_an_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/soubhiksanyal/RingNet "TensorFlow") [[project]](https://ringnet.is.tue.mpg.de/) 11 | - Boosting Local Shape Matching for Dense 3D Face Correspondence [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Fan_Boosting_Local_Shape_Matching_for_Dense_3D_Face_Correspondence_CVPR_2019_paper.pdf "CVPR2019") 12 | - **FML**: Face Model Learning From Videos [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Tewari_FML_Face_Model_Learning_From_Videos_CVPR_2019_paper.pdf "CVPR2019") -------------------------------------------------------------------------------- /docs/face_action.md: -------------------------------------------------------------------------------- 1 | ## 🔖Face Action 2 | - Joint Representation and Estimator Learning for Facial Action Unit Intensity Estimation [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang_Joint_Representation_and_Estimator_Learning_for_Facial_Action_Unit_Intensity_CVPR_2019_paper.pdf "CVPR2019") 3 | - Local Relationship Learning With Person-Specific Shape Regularization for Facial Action Unit Detection [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Niu_Local_Relationship_Learning_With_Person-Specific_Shape_Regularization_for_Facial_Action_CVPR_2019_paper.pdf "CVPR2019") 4 | - **TCAE**: Self-Supervised Representation Learning From Videos for Facial Action Unit Detection [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Li_Self-Supervised_Representation_Learning_From_Videos_for_Facial_Action_Unit_Detection_CVPR_2019_paper.pdf "CVPR2019 Oral") [[code]](https://github.com/mysee1989/TCAE "PyTorch") 5 | - **JAANet**: Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment [[paper]](http://openaccess.thecvf.com/content_ECCV_2018/papers/Zhiwen_Shao_Deep_Adaptive_Attention_ECCV_2018_paper.pdf "ECCV2018") [[code]](https://github.com/ZhiwenShao/JAANet "Caffe") -------------------------------------------------------------------------------- /docs/face_adversarial-attack.md: -------------------------------------------------------------------------------- 1 | ## 🔖Face Adversarial Attack 2 | - Decorrelated Adversarial Learning for Age-Invariant Face Recognition [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Wang_Decorrelated_Adversarial_Learning_for_Age-Invariant_Face_Recognition_CVPR_2019_paper.pdf "CVPR2019") 3 | - Multi-Adversarial Discriminative Deep Domain Generalization for Face Presentation Attack Detection [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Shao_Multi-Adversarial_Discriminative_Deep_Domain_Generalization_for_Face_Presentation_Attack_Detection_CVPR_2019_paper.pdf "CVPR2019") 4 | - Efficient Decision-Based Black-Box Adversarial Attacks on Face Recognition [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Dong_Efficient_Decision-Based_Black-Box_Adversarial_Attacks_on_Face_Recognition_CVPR_2019_paper.pdf "CVPR2019") -------------------------------------------------------------------------------- /docs/face_anti-spoofing.md: -------------------------------------------------------------------------------- 1 | ## 🔖Face Anti-Spoofing 2 | - **Dataset and Benchmark**: A Dataset and Benchmark for Large-Scale Multi-Modal Face Anti-Spoofing [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang_A_Dataset_and_Benchmark_for_Large-Scale_Multi-Modal_Face_Anti-Spoofing_CVPR_2019_paper.pdf "CVPR2019") [[poster]](http://www.cbsr.ia.ac.cn/users/sfzhang/Shifeng%20Zhang's%20Homepage_files/CVPR2019_CASIA-SURF_Poster.pdf) [[dataset]](https://sites.google.com/qq.com/chalearnfacespoofingattackdete/) 3 | - Deep Tree Learning for Zero-Shot Face Anti-Spoofing [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Liu_Deep_Tree_Learning_for_Zero-Shot_Face_Anti-Spoofing_CVPR_2019_paper.pdf "CVPR2019 Oral") -------------------------------------------------------------------------------- /docs/face_benchmark-and-dataset.md: -------------------------------------------------------------------------------- 1 | ## 🔖Face Benchmark and Dataset 2 | ### Face Recognition 3 | - **DiF**: Diversity in Faces [[project]](https://www.research.ibm.com/artificial-intelligence/trusted-ai/diversity-in-faces/) [[blog]](https://www.ibm.com/blogs/research/2019/01/diversity-in-faces/) 4 | - **FRVT**: Face Recognition Vendor Test [[project]](https://www.nist.gov/programs-projects/face-recognition-vendor-test-frvt) [[leaderboard]](https://www.nist.gov/programs-projects/face-recognition-vendor-test-frvt-ongoing) 5 | - **IMDb-Face**: The Devil of Face Recognition is in the Noise(**59k people in 1.7M images**) [[paper]](http://openaccess.thecvf.com/content_ECCV_2018/papers/Liren_Chen_The_Devil_of_ECCV_2018_paper.pdf "ECCV2018") [[dataset]](https://github.com/fwang91/IMDb-Face) 6 | - **Trillion Pairs**: Challenge 3: Face Feature Test/Trillion Pairs(**MS-Celeb-1M-v1c with 86,876 ids/3,923,399 aligned images + Asian-Celeb 93,979 ids/2,830,146 aligned images**) [[benckmark]](http://trillionpairs.deepglint.com/overview "DeepGlint") [[dataset]](http://trillionpairs.deepglint.com/data) [[result]](http://trillionpairs.deepglint.com/results) 7 | - **MF2**: Level Playing Field for Million Scale Face Recognition(**672K people in 4.7M images**) [[paper]](https://homes.cs.washington.edu/~kemelmi/ms.pdf "CVPR2017") [[dataset]](http://megaface.cs.washington.edu/dataset/download_training.html) [[result]](http://megaface.cs.washington.edu/results/facescrub_challenge2.html) [[benckmark]](http://megaface.cs.washington.edu/) 8 | - **MegaFace**: The MegaFace Benchmark: 1 Million Faces for Recognition at Scale(**690k people in 1M images**) [[paper]](http://megaface.cs.washington.edu/KemelmacherMegaFaceCVPR16.pdf "CVPR2016") [[dataset]](http://megaface.cs.washington.edu/participate/challenge.html) [[result]](http://megaface.cs.washington.edu/results/facescrub.html) [[benckmark]](http://megaface.cs.washington.edu/) 9 | - **UMDFaces**: An Annotated Face Dataset for Training Deep Networks(**8k people in 367k images with pose, 21 key-points and gender**) [[paper]](https://arxiv.org/pdf/1611.01484.pdf "arXiv2016") [[dataset]](http://www.umdfaces.io/) 10 | - **MS-Celeb-1M**: A Dataset and Benchmark for Large Scale Face Recognition(**100K people in 10M images**) [[paper]](https://arxiv.org/pdf/1607.08221.pdf "ECCV2016") [[dataset]](http://www.msceleb.org/download/sampleset) [[result]](http://www.msceleb.org/leaderboard/iccvworkshop-c1) [[benchmark]](http://www.msceleb.org/) [[project]](https://www.microsoft.com/en-us/research/project/ms-celeb-1m-challenge-recognizing-one-million-celebrities-real-world/) 11 | - **VGGFace2**: A dataset for recognising faces across pose and age(**9k people in 3.3M images**) [[paper]](https://arxiv.org/pdf/1710.08092.pdf "arXiv2017") [[dataset]](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/) 12 | - **VGGFace**: Deep Face Recognition(**2.6k people in 2.6M images**) [[paper]](http://www.robots.ox.ac.uk/~vgg/publications/2015/Parkhi15/parkhi15.pdf "BMVC2015") [[dataset]](http://www.robots.ox.ac.uk/~vgg/data/vgg_face/) 13 | - **CASIA-WebFace**: Learning Face Representation from Scratch(**10k people in 500k images**) [[paper]](https://arxiv.org/pdf/1411.7923.pdf "arXiv2014") [[dataset]](http://www.cbsr.ia.ac.cn/english/CASIA-WebFace-Database.html) 14 | - **LFW**: Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments(**5.7k people in 13k images**) [[report]](http://vis-www.cs.umass.edu/lfw/lfw.pdf "UMASS2007") [[dataset]](http://vis-www.cs.umass.edu/lfw/#download) [[result]](http://vis-www.cs.umass.edu/lfw/results.html) [[benchmark]](http://vis-www.cs.umass.edu/lfw/) 15 | 16 | ### Face Detection 17 | - **WiderFace**: WIDER FACE: A Face Detection Benchmark(**400k people in 32k images with a high degree of variability in scale, pose and occlusion**) [[paper]](https://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Yang_WIDER_FACE_A_CVPR_2016_paper.pdf "CVPR2016") [[dataset]](http://mmlab.ie.cuhk.edu.hk/projects/WIDERFace/) [[result]](http://mmlab.ie.cuhk.edu.hk/projects/WIDERFace/WiderFace_Results.html) [[benchmark]](http://mmlab.ie.cuhk.edu.hk/projects/WIDERFace/) 18 | - **FDDB**: A Benchmark for Face Detection in Unconstrained Settings(**5k faces in 2.8k images**) [[report]](https://people.cs.umass.edu/~elm/papers/fddb.pdf "UMASS2010") [[dataset]](http://vis-www.cs.umass.edu/fddb/index.html#download) [[result]](http://vis-www.cs.umass.edu/fddb/results.html) [[benchmark]](http://vis-www.cs.umass.edu/fddb/) 19 | 20 | ### Face Landmark 21 | - **LS3D-W**: A large-scale 3D face alignment dataset constructed by annotating the images from AFLW, 300VW, 300W and FDDB in a consistent manner with 68 points using the automatic method [[paper]](http://openaccess.thecvf.com/content_ICCV_2017/papers/Bulat_How_Far_Are_ICCV_2017_paper.pdf "ICCV2017") [[dataset]](https://adrianbulat.com/face-alignment) 22 | - **AFLW**: Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization(**25k faces with 21 landmarks**) [[paper]](https://files.icg.tugraz.at/seafhttp/files/460c7623-c919-4d35-b24e-6abaeacb6f31/koestinger_befit_11.pdf "BeFIT2011") [[benchmark]](https://www.tugraz.at/institute/icg/research/team-bischof/lrs/downloads/aflw/) 23 | 24 | ### Face Attribute 25 | - **CelebA**: Deep Learning Face Attributes in the Wild(**10k people in 202k images with 5 landmarks and 40 binary attributes per image**) [[paper]](https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Liu_Deep_Learning_Face_ICCV_2015_paper.pdf "ICCV2015") [[dataset]](http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html) -------------------------------------------------------------------------------- /docs/face_capture.md: -------------------------------------------------------------------------------- 1 | ## 🔖Face Capture 2 | - High-Quality Face Capture Using Anatomical Muscles [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Bao_High-Quality_Face_Capture_Using_Anatomical_Muscles_CVPR_2019_paper.pdf "CVPR2019") 3 | - Monocular Total Capture: Posing Face, Body, and Hands in the Wild [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Xiang_Monocular_Total_Capture_Posing_Face_Body_and_Hands_in_the_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/CMU-Perceptual-Computing-Lab/MonocularTotalCapture) [[project]](http://domedb.perception.cs.cmu.edu/mtc.html) 4 | - Expressive Body Capture: 3D Hands, Face, and Body From a Single Image [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Pavlakos_Expressive_Body_Capture_3D_Hands_Face_and_Body_From_a_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/vchoutas/smplify-x "PyTorch") [[project]](https://smpl-x.is.tue.mpg.de/) -------------------------------------------------------------------------------- /docs/face_clustering.md: -------------------------------------------------------------------------------- 1 | ## 🔖Face Clustering 2 | - **LinkageFace**: Linkage Based Face Clustering via Graph Convolution Network [[paper]](https://arxiv.org/abs/1903.11306 "CVPR2019") 3 | - **LTC**: Learning to Cluster Faces on an Affinity Graph [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yang_Learning_to_Cluster_Faces_on_an_Affinity_Graph_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/yl-1993/learn-to-cluster "PyTorch") -------------------------------------------------------------------------------- /docs/face_cross-modal.md: -------------------------------------------------------------------------------- 1 | ## 🔖Face Cross-Modal 2 | - **Speech2Face**: Learning the Face Behind a Voice [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Oh_Speech2Face_Learning_the_Face_Behind_a_Voice_CVPR_2019_paper.pdf "CVPR2019") [[project]](https://speech2face.github.io/) 3 | - **JFDFMR**: Joint Face Detection and Facial Motion Retargeting for Multiple Faces [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Chaudhuri_Joint_Face_Detection_and_Facial_Motion_Retargeting_for_Multiple_Faces_CVPR_2019_paper.pdf "CVPR2019") 4 | - **ATVGnet**: Hierarchical Cross-Modal Talking Face Generation With Dynamic Pixel-Wise Loss [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Chen_Hierarchical_Cross-Modal_Talking_Face_Generation_With_Dynamic_Pixel-Wise_Loss_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/lelechen63/ATVGnet "PyTorch") -------------------------------------------------------------------------------- /docs/face_detection.md: -------------------------------------------------------------------------------- 1 | ## 🔖Face Detection 2 | - **RetinaFace**: Single-stage Dense Face Localisation in the Wild [[paper]](https://arxiv.org/abs/1905.00641 "arXiv2019") [[code]](https://github.com/deepinsight/insightface/tree/master/RetinaFace "MXNet") 3 | - Group Sampling for Scale Invariant Face Detection [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Ming_Group_Sampling_for_Scale_Invariant_Face_Detection_CVPR_2019_paper.pdf "CVPR2019") 4 | - **FA-RPN**: Floating Region Proposals for Face Detection [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Najibi_FA-RPN_Floating_Region_Proposals_for_Face_Detection_CVPR_2019_paper.pdf "CVPR2019") 5 | - **SFA**: Small Faces Attention Face Detector [[paper]](https://arxiv.org/abs/1812.08402 "SPIC2019") [[code]](https://github.com/shiluo1990/SFA "Caffe") 6 | - **ISRN**: Improved Selective Refinement Network for Face Detection [[paper]](https://arxiv.org/abs/1901.06651 "arXiv2019") 7 | - **DSFD**: Dual Shot Face Detector [[paper]](https://arxiv.org/abs/1810.10220 "CVPR2019") [[code]](https://github.com/TencentYoutuResearch/FaceDetection-DSFD "PyTorch") 8 | - **PyramidBox++**: High Performance Detector for Finding Tiny Face [[paper]](https://arxiv.org/abs/1904.00386 "arXiv2019") 9 | - **VIM-FD**: Robust and High Performance Face Detector [[paper]](https://arxiv.org/abs/1901.02350 "arXiv2019") 10 | - **SHF**: Robust Face Detection via Learning Small Faces on Hard Images [[paper]](https://arxiv.org/abs/1811.11662 "arXiv2018") [[code]](https://github.com/bairdzhang/smallhardface "Caffe") 11 | - **SRN**: Selective Refinement Network for High Performance Face Detection [[paper]](https://arxiv.org/abs/1809.02693 "AAAI2019") 12 | - **SFDet**: Single-Shot Scale-Aware Network for Real-Time Face Detection [[paper]](https://link.springer.com/epdf/10.1007/s11263-019-01159-3?author_access_token=Jjgl-u1CAXPmSKWDljfSBfe4RwlQNchNByi7wbcMAY7Vwo_nrkuFMElF6YSQ0We34tUs42D0dyurcBAD0sJP66n6GBanVgA9qsuvh4Y_Bjf3E_n9_croQ4esS882srfHyUz-L96pU3gu_M30Kk6_XQ%3D%3D "IJCV2019") 13 | - **HyperFace**: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition [[paper]](https://arxiv.org/abs/1603.01249 "TPAMI2019") [[code]](https://github.com/maharshi95/HyperFace "TensorFlow") 14 | - **PyramidBox**: A Context-assisted Single Shot Face Detector [[paper]](https://arxiv.org/pdf/1803.07737.pdf "arXiv2018") [[code]](https://github.com/PaddlePaddle/models/tree/2a6b7dc92f04815f0b298e59030cb779dd0e038c/fluid/face_detction "PaddlePaddle") 15 | - **PCN**: Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks [[paper]](https://arxiv.org/pdf/1804.06039.pdf "CVPR2018") [[code]](https://github.com/Jack-CV/PCN "C++") 16 | - **S³FD**: Single Shot Scale-invariant Face Detector [[paper]](https://arxiv.org/pdf/1708.05237.pdf "arXiv2017") [[code]](https://github.com/sfzhang15/SFD "Caffe") 17 | - **SSH**: Single Stage Headless Face Detector [[paper]](http://openaccess.thecvf.com/content_ICCV_2017/papers/Najibi_SSH_Single_Stage_ICCV_2017_paper.pdf "ICCV2017") [[code]](https://github.com/mahyarnajibi/SSH "Caffe") 18 | - **FaceBoxes**: A CPU Real-time Face Detector with High Accuracy [[paper]](https://arxiv.org/pdf/1708.05234.pdf "IJCB2017")[[code1]](https://github.com/zeusees/FaceBoxes "Caffe") [[code2]](https://github.com/lxg2015/faceboxes "PyTorch") 19 | - **TinyFace**: Finding Tiny Faces [[paper]](http://openaccess.thecvf.com/content_cvpr_2017/papers/Hu_Finding_Tiny_Faces_CVPR_2017_paper.pdf "CVPR2017") [[project]](https://www.cs.cmu.edu/~peiyunh/tiny/) [[code1]](https://github.com/peiyunh/tiny "MatConvNet") [[code2]](https://github.com/chinakook/hr101_mxnet "MXNet") [[code3]](https://github.com/cydonia999/Tiny_Faces_in_Tensorflow "TensorFlow") 20 | - **MTCNN**: Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks [[paper]](https://kpzhang93.github.io/MTCNN_face_detection_alignment/paper/spl.pdf "SPL2016") [[project]](https://kpzhang93.github.io/MTCNN_face_detection_alignment/) [[code1]](https://github.com/kpzhang93/MTCNN_face_detection_alignment "Caffe") [[code2]](https://github.com/CongWeilin/mtcnn-caffe "Caffe") [[code3]](https://github.com/foreverYoungGitHub/MTCNN "Caffe") [[code4]](https://github.com/Seanlinx/mtcnn "MXNet") [[code5]](https://github.com/pangyupo/mxnet_mtcnn_face_detection "MXNet") [[code6]](https://github.com/TropComplique/mtcnn-pytorch "PyTorch") [[code7]](https://github.com/AITTSMD/MTCNN-Tensorflow "TensorFlow") 21 | - **NPD**: A Fast and Accurate Unconstrained Face Detector [[paper]](http://www.cbsr.ia.ac.cn/users/scliao/papers/Liao-PAMI15-NPD.pdf "TPAMI2015") [[code]](https://github.com/wincle/NPD "C++") [[project]](http://www.cbsr.ia.ac.cn/users/scliao/projects/npdface/index.html) 22 | - **PICO**: Object Detection with Pixel Intensity Comparisons Organized in Decision Trees [[paper]](https://arxiv.org/pdf/1305.4537.pdf "arXiv2014") [[code]](https://github.com/nenadmarkus/pico "C") 23 | - **libfacedetection**: A fast binary library for face detection and face landmark detection in images. [[code]](https://github.com/ShiqiYu/libfacedetection "C++") 24 | - **SeetaFaceEngine**: SeetaFace Detection, SeetaFace Alignment and SeetaFace Identification [[code]](https://github.com/seetaface/SeetaFaceEngine "C++") -------------------------------------------------------------------------------- /docs/face_expression.md: -------------------------------------------------------------------------------- 1 | ## 🔖Face Expression 2 | - **FECNet**: A Compact Embedding for Facial Expression Similarity [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Vemulapalli_A_Compact_Embedding_for_Facial_Expression_Similarity_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/GerardLiu96/FECNet "Keras") 3 | - **LBVCNN**: Local Binary Volume Convolutional Neural Network for Facial Expression Recognition from Image Sequences [[paper]](https://arxiv.org/abs/1904.07647 "arXiv2019") -------------------------------------------------------------------------------- /docs/face_gan.md: -------------------------------------------------------------------------------- 1 | ## 🔖Face GAN 2 | #### Face Aging 3 | - Automatic Face Aging in Videos via Deep Reinforcement Learning [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Duong_Automatic_Face_Aging_in_Videos_via_Deep_Reinforcement_Learning_CVPR_2019_paper.pdf "CVPR2019") [[blog]](https://www.fastcompany.com/90314606/this-new-ai-tool-makes-creepily-realistic-videos-of-faces-in-the-future) 4 | - Attribute-Aware Face Aging With Wavelet-Based Generative Adversarial Networks [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Liu_Attribute-Aware_Face_Aging_With_Wavelet-Based_Generative_Adversarial_Networks_CVPR_2019_paper.pdf "CVPR2019") 5 | - **SAGAN**: Generative Adversarial Network with Spatial Attention for Face Attribute Editing [[paper]](http://openaccess.thecvf.com/content_ECCV_2018/papers/Gang_Zhang_Generative_Adversarial_Network_ECCV_2018_paper.pdf "ECCV2018") [[code]](https://github.com/elvisyjlin/SpatialAttentionGAN "PyTorch") 6 | 7 | --- 8 | #### Face Drawing 9 | - **APDrawingGAN**: Generating Artistic Portrait Drawings From Face Photos With Hierarchical GANs [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yi_APDrawingGAN_Generating_Artistic_Portrait_Drawings_From_Face_Photos_With_Hierarchical_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/yiranran/APDrawingGAN "PyTorch") 10 | 11 | --- 12 | #### Face Generation 13 | - **StyleGAN**: A Style-Based Generator Architecture for Generative Adversarial Networks [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Karras_A_Style-Based_Generator_Architecture_for_Generative_Adversarial_Networks_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/NVlabs/stylegan "TensorFlow") [[dataset]](https://github.com/NVlabs/ffhq-dataset "FFHQ") 14 | 15 | --- 16 | #### Face Makeup 17 | - **BeautyGAN**: Instance-level Facial Makeup Transfer with Deep Generative Adversarial Network [[paper]](http://liusi-group.com/pdf/BeautyGAN-camera-ready_2.pdf "Multimedia Conference, ACM2018") [[code]](https://github.com/Honlan/BeautyGAN "TensorFlow") [[project]](http://liusi-group.com/projects/BeautyGAN) [[poster]](http://liusi-group.com/pdf/BeautyGAN-camera-ready_2_poster.pdf) 18 | 19 | --- 20 | #### Face Swap 21 | - **Faceswap**: A tool that utilizes deep learning to recognize and swap faces in pictures and videos [[code1]](https://github.com/deepfakes/faceswap "TensorFlow") [[code2]](https://github.com/iperov/DeepFaceLab "TensorFlow/Keras") 22 | - **FUNIT**: Few-Shot Unsupervised Image-to-Image Translation [[paper]](https://arxiv.org/abs/1905.01723 "arXiv2019") [[code]](https://github.com/NVlabs/FUNIT "PyTorch") [[project]](https://nvlabs.github.io/FUNIT/) 23 | 24 | --- 25 | - Unsupervised Face Normalization With Extreme Pose and Expression in the Wild [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Qian_Unsupervised_Face_Normalization_With_Extreme_Pose_and_Expression_in_the_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/mx54039q/fnm "TensorFlow") 26 | - **GANFIT**: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Gecer_GANFIT_Generative_Adversarial_Network_Fitting_for_High_Fidelity_3D_Face_CVPR_2019_paper.pdf "CVPR2019") [[project]](https://github.com/barisgecer/GANFit) 27 | - **HF-PIM**: Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization [[paper]](http://papers.nips.cc/paper/7551-learning-a-high-fidelity-pose-invariant-model-for-high-resolution-face-frontalization.pdf "NIPS2018") 28 | - **Super-FAN**: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs [[paper]](http://openaccess.thecvf.com/content_cvpr_2018/papers/Bulat_Super-FAN_Integrated_Facial_CVPR_2018_paper.pdf "CVPR2018 Spotlight") 29 | - **GANimation**: Anatomically-aware Facial Animation from a Single Image [[paper]](https://www.albertpumarola.com/publications/files/pumarola2018ganimation.pdf "ECCV2018 Oral,Best Paper Award Honorable Mention") [[project]](https://www.albertpumarola.com/research/GANimation/index.html) [[code]](https://github.com/albertpumarola/GANimation "PyTorch") 30 | - **StarGAN**: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation [[paper]](http://openaccess.thecvf.com/content_cvpr_2018/papers/Choi_StarGAN_Unified_Generative_CVPR_2018_paper.pdf "CVPR2018") 31 | [[code]](https://github.com/yunjey/StarGAN "PyTorch") 32 | - **PGAN**: Progressive Growing of GANs for Improved Quality, Stability, and Variation [[paper]](https://arxiv.org/abs/1710.10196 "ICLR2018") 33 | [[code1]](https://github.com/tkarras/progressive_growing_of_gans "TensorFlow") [[code2]](https://github.com/github-pengge/PyTorch-progressive_growing_of_gans "PyTorch") -------------------------------------------------------------------------------- /docs/face_landmark.md: -------------------------------------------------------------------------------- 1 | ## 🔖Face Landmark 2 | - **Semantic Alignment**: Finding Semantically Consistent Ground-Truth for Facial Landmark Detection [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Liu_Semantic_Alignment_Finding_Semantically_Consistent_Ground-Truth_for_Facial_Landmark_Detection_CVPR_2019_paper.pdf "CVPR2019") 3 | - Robust Facial Landmark Detection via Occlusion-Adaptive Deep Networks [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhu_Robust_Facial_Landmark_Detection_via_Occlusion-Adaptive_Deep_Networks_CVPR_2019_paper.pdf "CVPR2019") 4 | - **PFLD**: A Practical Facial Landmark Detector [[paper]](https://arxiv.org/abs/1902.10859 "arXiv2019") [[project]](https://sites.google.com/view/xjguo/fld) [[code]](https://drive.google.com/file/d/1n1uZPbM9Wz052aVnlc_3L4gjQHiwfj4B/view "APK") 5 | - **PRNet**: Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network [[paper]](http://openaccess.thecvf.com/content_ECCV_2018/papers/Yao_Feng_Joint_3D_Face_ECCV_2018_paper.pdf "ECCV2018") [[code]](https://github.com/YadiraF/PRNet "TensorFlow") 6 | - **LAB**: Look at Boundary: A Boundary-Aware Face Alignment Algorithm [[paper]](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Look_at_Boundary_CVPR_2018_paper.pdf "CVPR2018") [[project]](https://wywu.github.io/projects/LAB/LAB.html) [[code]](https://github.com/wywu/LAB "Caffe") 7 | - **Face-Alignment**: How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks) [[paper]](http://openaccess.thecvf.com/content_ICCV_2017/papers/Bulat_How_Far_Are_ICCV_2017_paper.pdf "ICCV2017") [[project]](https://adrianbulat.com/face-alignment) [[code1]](https://github.com/1adrianb/face-alignment "PyTorch") [[code2]](https://github.com/1adrianb/2D-and-3D-face-alignment "Torch7") 8 | - **ERT**: One Millisecond Face Alignment with an Ensemble of Regression Trees [[paper]](https://www.cv-foundation.org/openaccess/content_cvpr_2014/papers/Kazemi_One_Millisecond_Face_2014_CVPR_paper.pdf "CVPR2014") [[code]](http://dlib.net/imaging.html "Dlib") -------------------------------------------------------------------------------- /docs/face_lib-and-tool.md: -------------------------------------------------------------------------------- 1 | ## Face Lib&Tool 2 | - **Dlib** [[url]](http://dlib.net/imaging.html "Image Processing") [[github]](https://github.com/davisking/dlib "master") 3 | - **OpenCV** [[docs]](https://docs.opencv.org "All Versions") [[github]](https://github.com/opencv/opencv/ "master") 4 | - **Face3D** [[github]](https://github.com/YadiraF/face3d "master") -------------------------------------------------------------------------------- /docs/face_manipulation.md: -------------------------------------------------------------------------------- 1 | ## 🔖Face Manipulation 2 | - 3D Guided Fine-Grained Face Manipulation [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Geng_3D_Guided_Fine-Grained_Face_Manipulation_CVPR_2019_paper.pdf "CVPR2019") 3 | - **SemanticComponent**: Semantic Component Decomposition for Face Attribute Manipulation [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Chen_Semantic_Component_Decomposition_for_Face_Attribute_Manipulation_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/yingcong/SemanticComponent) [[demo]](http://appsrv.cse.cuhk.edu.hk/~ycchen/demos/semantic_component.mp4) -------------------------------------------------------------------------------- /docs/face_recognition.md: -------------------------------------------------------------------------------- 1 | ## 🔖Face Recognition 2 | - Deep face recognition using imperfect facial data [[paper]](https://www.sciencedirect.com/science/article/pii/S0167739X18331133 "FGCS2019") 3 | - Unequal-Training for Deep Face Recognition With Long-Tailed Noisy Data [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhong_Unequal-Training_for_Deep_Face_Recognition_With_Long-Tailed_Noisy_Data_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/zhongyy/Unequal-Training-for-Deep-Face-Recognition-with-Long-Tailed-Noisy-Data "MXNet") 4 | - **RegularFace**: Deep Face Recognition via Exclusive Regularization [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhao_RegularFace_Deep_Face_Recognition_via_Exclusive_Regularization_CVPR_2019_paper.pdf "CVPR2019") 5 | - **UniformFace**: Learning Deep Equidistributed Representation for Face Recognition [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Duan_UniformFace_Learning_Deep_Equidistributed_Representation_for_Face_Recognition_CVPR_2019_paper.pdf "CVPR2019") 6 | - **P2SGrad**: Refined Gradients for Optimizing Deep Face Models [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang_P2SGrad_Refined_Gradients_for_Optimizing_Deep_Face_Models_CVPR_2019_paper.pdf "CVPR2019") 7 | - **AdaptiveFace**: Adaptive Margin and Sampling for Face Recognition [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Liu_AdaptiveFace_Adaptive_Margin_and_Sampling_for_Face_Recognition_CVPR_2019_paper.pdf "CVPR2019") 8 | - **AdaCos**: Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representations [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang_AdaCos_Adaptively_Scaling_Cosine_Logits_for_Effectively_Learning_Deep_Face_CVPR_2019_paper.pdf "CVPR2019") [[code1]](https://github.com/xialuxi/arcface-caffe "Caffe") [[code2]](https://github.com/4uiiurz1/pytorch-adacos "PyTorch") 9 | - Low-Rank Laplacian-Uniform Mixed Model for Robust Face Recognition [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Dong_Low-Rank_Laplacian-Uniform_Mixed_Model_for_Robust_Face_Recognition_CVPR_2019_paper.pdf "CVPR2019") 10 | - **NoiseFace**: Noise-Tolerant Paradigm for Training Face Recognition CNNs [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Hu_Noise-Tolerant_Paradigm_for_Training_Face_Recognition_CNNs_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/huangyangyu/NoiseFace "Caffe") 11 | - Feature Transfer Learning for Face Recognition With Under-Represented Data [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yin_Feature_Transfer_Learning_for_Face_Recognition_With_Under-Represented_Data_CVPR_2019_paper.pdf "CVPR2019") 12 | - **Led3D**: A Lightweight and Efficient Deep Approach to Recognizing Low-Quality 3D Faces [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Mu_Led3D_A_Lightweight_and_Efficient_Deep_Approach_to_Recognizing_Low-Quality_CVPR_2019_paper.pdf "CVPR2019") [[code]](https://github.com/muyouhang/Led3D "NULL") [[dataset]](http://irip.buaa.edu.cn/lock3dface/index.html) 13 | - R3 Adversarial Network for Cross Model Face Recognition [[paper]](http://openaccess.thecvf.com/content_CVPR_2019/papers/Chen_R3_Adversarial_Network_for_Cross_Model_Face_Recognition_CVPR_2019_paper.pdf "CVPR2019") 14 | - **MLT**: Face Recognition: A Novel Multi-Level Taxonomy based Survey [[paper]](https://arxiv.org/abs/1901.00713 "arXiv2019") 15 | - **GhostVLAD**: GhostVLAD for set-based face recognition [[paper]](https://arxiv.org/abs/1810.09951 "ACCV2018") 16 | - **DocFace+**: ID Document to Selfie Matching [[paper]](https://arxiv.org/abs/1809.05620 "arXiv2018") [[code]](https://github.com/seasonSH/DocFace "TensorFlow") 17 | - **2018Survey**: Face Recognition: From Traditional to Deep Learning Methods [[paper]](https://arxiv.org/abs/1811.00116 "arXiv2018") 18 | - **2018Survey**: Deep Facial Expression Recognition: A Survey [[paper]](https://arxiv.org/abs/1804.08348 "arXiv2018") 19 | - **2018Survey**: Deep Face Recognition: A Survey [[paper]](https://arxiv.org/abs/1804.06655 "arXiv2018") 20 | - **SphereFace+(MHE)**: Learning towards Minimum Hyperspherical Energy [[paper]](https://arxiv.org/abs/1805.09298 "arXiv2018") [[code]](https://github.com/wy1iu/sphereface-plus "Caffe/Matlab") 21 | - **MobileFace**: A face recognition solution on mobile device [[code]](https://github.com/becauseofAI/MobileFace) 22 | - **MobileFaceNets**: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices [[paper]](https://arxiv.org/abs/1804.07573 "arXiv2018") [[code1]](https://github.com/deepinsight/insightface "MXNet") [[code2]](https://github.com/KaleidoZhouYN/mobilefacenet-caffe "Caffe") [[code3]](https://github.com/xsr-ai/MobileFaceNet_TF "TensorFlow") [[code4]](https://github.com/GRAYKEY/mobilefacenet_ncnn "NCNN") 23 | - **FaceID**: An implementation of iPhone X's FaceID using face embeddings and siamese networks on RGBD images. [[code]](https://github.com/normandipalo/faceID_beta "Keras") [[blog]](https://towardsdatascience.com/how-i-implemented-iphone-xs-faceid-using-deep-learning-in-python-d5dbaa128e1d "Medium") 24 | - **InsightFace(ArcFace)**: 2D and 3D Face Analysis Project [[paper]](https://arxiv.org/abs/1801.07698 "ArcFace: Additive Angular Margin Loss for Deep Face Recognition(arXiv)") [[code1]](https://github.com/deepinsight/insightface "MXNet") [[code2]](https://github.com/auroua/InsightFace_TF "TensorFlow") 25 | - **AAM-Softmax(CCL)**: Face Recognition via Centralized Coordinate Learning [[paper]](https://arxiv.org/abs/1801.05678 "arXiv2018") 26 | - **AM-Softmax**: Additive Margin Softmax for Face Verification [[paper]](https://arxiv.org/abs/1801.05599 "arXiv2018") [[code1]](https://github.com/happynear/AMSoftmax "Caffe") [[code2]](https://github.com/Joker316701882/Additive-Margin-Softmax "TensorFlow") 27 | - **CosFace**: Large Margin Cosine Loss for Deep Face Recognition [[paper]](https://arxiv.org/abs/1801.09414 "CVPR2018") [[code1]](https://github.com/deepinsight/insightface "MXNet") [[code2]](https://github.com/yule-li/CosFace "TensorFlow") 28 | - **FeatureIncay**: Feature Incay for Representation Regularization [[paper]](https://arxiv.org/abs/1705.10284 "ICLR2018") 29 | - **CocoLoss**: Rethinking Feature Discrimination and Polymerization for Large-scale Recognition [[paper]](http://cn.arxiv.org/abs/1710.00870 "NIPS2017") [[code]](https://github.com/sciencefans/coco_loss "Caffe") 30 | - **NormFace**: L2 hypersphere embedding for face Verification [[paper]](http://www.cs.jhu.edu/~alanlab/Pubs17/wang2017normface.pdf "ACM2017 Multimedia Conference") [[code]](https://github.com/happynear/NormFace "Caffe") 31 | - **SphereFace(A-Softmax)**: Deep Hypersphere Embedding for Face Recognition [[paper]](http://openaccess.thecvf.com/content_cvpr_2017/papers/Liu_SphereFace_Deep_Hypersphere_CVPR_2017_paper.pdf "CVPR2017") [[code]](https://github.com/wy1iu/sphereface "Caffe") 32 | - **L-Softmax**: Large-Margin Softmax Loss for Convolutional Neural Networks [[paper]](http://proceedings.mlr.press/v48/liud16.pdf "ICML2016") [[code1]](https://github.com/wy1iu/LargeMargin_Softmax_Loss "Caffe") [[code2]](https://github.com/luoyetx/mx-lsoftmax "MXNet") [[code3]](https://github.com/HiKapok/tf.extra_losses "TensorFlow") [[code4]](https://github.com/auroua/L_Softmax_TensorFlow "TensorFlow") [[code5]](https://github.com/tpys/face-recognition-caffe2 "Caffe2") [[code6]](https://github.com/amirhfarzaneh/lsoftmax-pytorch "PyTorch") [[code7]](https://github.com/jihunchoi/lsoftmax-pytorch "PyTorch") 33 | - **CenterLoss**: A Discriminative Feature Learning Approach for Deep Face Recognition [[paper]](https://ydwen.github.io/papers/WenECCV16.pdf "ECCV2016") [[code1]](https://github.com/ydwen/caffe-face "Caffe") [[code2]](https://github.com/pangyupo/mxnet_center_loss "MXNet") [[code3]](https://github.com/ShownX/mxnet-center-loss "MXNet-Gluon") [[code4]](https://github.com/EncodeTS/TensorFlow_Center_Loss "TensorFlow") 34 | - **OpenFace**: A general-purpose face recognition library with mobile applications [[report]](http://elijah.cs.cmu.edu/DOCS/CMU-CS-16-118.pdf "CMU2016") [[project]](http://cmusatyalab.github.io/openface/) [[code1]](https://github.com/cmusatyalab/openface "Torch") [[code2]](https://github.com/thnkim/OpenFacePytorch "PyTorch") 35 | - **FaceNet**: A Unified Embedding for Face Recognition and Clustering [[paper]](https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Schroff_FaceNet_A_Unified_2015_CVPR_paper.pdf "CVPR2015") [[code]](https://github.com/davidsandberg/facenet "TensorFlow") 36 | - **DeepID3**: DeepID3: Face Recognition with Very Deep Neural Networks [[paper]](https://arxiv.org/abs/1502.00873 "arXiv2015") 37 | - **DeepID2+**: Deeply learned face representations are sparse, selective, and robust [[paper]](https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Sun_Deeply_Learned_Face_2015_CVPR_paper.pdf "CVPR2015") 38 | - **DeepID2**: Deep Learning Face Representation by Joint Identification-Verification [[paper]](https://papers.nips.cc/paper/5416-deep-learning-face-representation-by-joint-identification-verification.pdf "NIPS2014") 39 | - **DeepID**: Deep Learning Face Representation from Predicting 10,000 Classes [[paper]](https://www.cv-foundation.org/openaccess/content_cvpr_2014/papers/Sun_Deep_Learning_Face_2014_CVPR_paper.pdf "CVPR2014") 40 | - **DeepFace**: Closing the gap to human-level performance in face verification [[paper]](https://www.cv-foundation.org/openaccess/content_cvpr_2014/papers/Taigman_DeepFace_Closing_the_2014_CVPR_paper.pdf "CVPR2014") 41 | - **LBP+Joint Bayes**: Bayesian Face Revisited: A Joint Formulation [[paper]](https://s3.amazonaws.com/academia.edu.documents/31414608/JointBayesian.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1543656042&Signature=k6LefuQnIC2x8gep7yQTxqKgzus%3D&response-content-disposition=inline%3B%20filename%3DBayesian_Face_Revisited_A_Joint_Formulat.pdf "ECCV2012") [[code1]](https://github.com/cyh24/Joint-Bayesian "Python") [[code2]](https://github.com/MaoXu/Joint_Bayesian "Matlab") [[code3]](https://github.com/Glasssix/joint_bayesian "C++/C#") 42 | - **LBPFace**: Face recognition with local binary patterns [[paper]](https://pdfs.semanticscholar.org/3242/0c65f8ef0c5bd83b14c8ae662cbce73e6781.pdf "ECCV2004") [[code]](https://docs.opencv.org/2.4/modules/contrib/doc/facerec/facerec_tutorial.html "OpenCV") 43 | - **FisherFace(LDA)**: Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection [[paper]](https://apps.dtic.mil/dtic/tr/fulltext/u2/1015508.pdf "TPAMI1997") [[code]](https://docs.opencv.org/2.4/modules/contrib/doc/facerec/facerec_tutorial.html "OpenCV") 44 | - **EigenFace(PCA)**: Face recognition using eigenfaces [[paper]](http://www.cs.ucsb.edu/~mturk/Papers/mturk-CVPR91.pdf "CVPR1991") [[code]](https://docs.opencv.org/2.4/modules/contrib/doc/facerec/facerec_tutorial.html "OpenCV") 45 | -------------------------------------------------------------------------------- /js/baidu-tongji.js: -------------------------------------------------------------------------------- 1 | var _hmt = _hmt || []; 2 | (function() { 3 | var hm = document.createElement("script"); 4 | hm.src = "https://hm.baidu.com/hm.js?4090a2fa04d7855959f2f47a04ba1cc3"; 5 | var s = document.getElementsByTagName("script")[0]; 6 | s.parentNode.insertBefore(hm, s); 7 | })(); 8 | 9 | -------------------------------------------------------------------------------- /js/extra.js: -------------------------------------------------------------------------------- 1 | window.MathJax = { 2 | tex2jax: { 3 | inlineMath: [ ["\\(","\\)"] ], 4 | displayMath: [ ["\\[","\\]"] ] 5 | }, 6 | TeX: { 7 | TagSide: "right", 8 | TagIndent: ".8em", 9 | MultLineWidth: "85%", 10 | equationNumbers: { 11 | autoNumber: "AMS", 12 | }, 13 | unicode: { 14 | fonts: "STIXGeneral,'Arial Unicode MS'" 15 | } 16 | }, 17 | displayAlign: "left", 18 | showProcessingMessages: false, 19 | messageStyle: "none" 20 | }; 21 | -------------------------------------------------------------------------------- /mkdocs-material.yml: -------------------------------------------------------------------------------- 1 | site_name: Hello Face 2 | site_url: https://becauseofAI.github.io/hello-face/ 3 | site_description: Face Technology Repository. 4 | site_author: becauseofAI 5 | 6 | repo_url: https://github.com/becauseofAI/hello-face/ 7 | edit_uri: "" 8 | repo_name: 'HelloFace' 9 | 10 | theme: 11 | name: material 12 | palette: 13 | primary: 'Blue Grey' 14 | accent: 'Pink' 15 | feature: 16 | tabs: false 17 | #font: 18 | #text: 'Ubuntu' 19 | #code: 'Ubuntu Mono' 20 | language: 'zh' 21 | 22 | extra: 23 | social: 24 | - type: github 25 | link: https://github.com/becauseofAI 26 | search: 27 | language: 'ja' 28 | 29 | markdown_extensions: 30 | - admonition 31 | - codehilite: 32 | guess_lang: false 33 | linenums: false 34 | - toc: 35 | permalink: true 36 | - footnotes 37 | - meta 38 | - def_list 39 | - pymdownx.arithmatex 40 | - pymdownx.betterem: 41 | smart_enable: all 42 | - pymdownx.caret 43 | - pymdownx.critic 44 | - pymdownx.details 45 | - pymdownx.emoji: 46 | emoji_generator: !!python/name:pymdownx.emoji.to_png 47 | #emoji_generator: !!python/name:pymdownx.emoji.to_svg 48 | #emoji_generator: !!python/name:pymdownx.emoji.to_png_sprite 49 | #emoji_generator: !!python/name:pymdownx.emoji.to_svg_sprite 50 | #emoji_generator: !!python/name:pymdownx.emoji.to_awesome 51 | #emoji_generator: !!python/name:pymdownx.emoji.to_alt 52 | - pymdownx.inlinehilite 53 | - pymdownx.magiclink 54 | - pymdownx.mark 55 | - pymdownx.smartsymbols 56 | - pymdownx.superfences 57 | - pymdownx.tasklist 58 | - pymdownx.tilde 59 | 60 | extra_javascript: 61 | - './js/extra.js' 62 | - './js/baidu-tongji.js' 63 | - 'https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-MML-AM_CHTML' 64 | 65 | extra_css: 66 | - './css/extra.css' 67 | 68 | copyright: Copyright © 2019 becauseofAI, Maintained by the becauseofAI. 69 | google_analytics: ['UA-27795084-5', 'mkdocs.org'] 70 | 71 | plugins: 72 | - search 73 | # - mknotebooks: 74 | # execute: false 75 | # preamble: "pandas_to_markdown.py" 76 | 77 | nav: 78 | - HelloFace: index.md 79 | - Face Recognition: face_recognition.md 80 | - Face Detection: face_detection.md 81 | - Face Landmark: face_landmark.md 82 | - Face Clustering: face_clustering.md 83 | - Face Expression: face_expression.md 84 | - Face Action: face_action.md 85 | - Face 3D: face_3d.md 86 | - Face GAN: face_gan.md 87 | - Face Manipulation: face_manipulation.md 88 | - Face Anti-Spoofing: face_anti-spoofing.md 89 | - Face Adversarial Attack: face_adversarial-attack.md 90 | - Face Cross-Modal: face_cross-modal.md 91 | - Face Capture: face_capture.md 92 | - Face Benchmark&Dataset: face_benchmark-and-dataset.md 93 | - Face Lib&Tool: face_lib-and-tool.md 94 | - About: about.md 95 | # - Release Notes: about/release-notes.md 96 | # - Contributing: about/contributing.md 97 | # - License: about/license.md -------------------------------------------------------------------------------- /mkdocs-readthedocs.yml: -------------------------------------------------------------------------------- 1 | site_name: Hello Face 2 | site_url: https://hello-face.readthedocs.io 3 | site_description: Face Technology Repository. 4 | site_author: becauseofAI 5 | 6 | repo_url: https://github.com/becauseofAI/hello-face/ 7 | edit_uri: "" 8 | repo_name: 'HelloFace' 9 | 10 | theme: 11 | name: mkdocs 12 | highlightjs: true 13 | hljs_languages: 14 | - yaml 15 | - django 16 | 17 | markdown_extensions: 18 | - toc: 19 | permalink:  20 | - admonition 21 | - def_list 22 | # - mdx_gh_links: 23 | # user: mkdocs 24 | # repo: mkdocs 25 | 26 | extra_javascript: 27 | - './js/extra.js' 28 | - './js/baidu-tongji.js' 29 | - 'https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-MML-AM_CHTML' 30 | 31 | extra_css: 32 | - './css/extra.css' 33 | 34 | copyright: Copyright © 2019 becauseofAI, Maintained by the becauseofAI. 35 | google_analytics: ['UA-27795084-5', 'mkdocs.org'] 36 | 37 | plugins: 38 | - search 39 | 40 | # nav: 41 | # - Introduction: index.md 42 | # - Tutorials: 43 | # - Ghapter01 Getting Started: chapter01_getting-started/README.md 44 | # - Ghapter02 Basics: chapter02_basics/README.md 45 | # - About: about.md 46 | # # - Release Notes: about/release-notes.md 47 | # # - Contributing: about/contributing.md 48 | # # - License: about/license.md 49 | 50 | nav: 51 | - HelloFace: index.md 52 | - Face Recognition: face_recognition.md 53 | - Face Detection: face_detection.md 54 | - Face Landmark: face_landmark.md 55 | - Face Clustering: face_clustering.md 56 | - Face Expression: face_expression.md 57 | - Face Action: face_action.md 58 | - Face 3D: face_3d.md 59 | - Face GAN: face_gan.md 60 | - Face Manipulation: face_manipulation.md 61 | - Face Anti-Spoofing: face_anti-spoofing.md 62 | - Face Adversarial Attack: face_adversarial-attack.md 63 | - Face Cross-Modal: face_cross-modal.md 64 | - Face Capture: face_capture.md 65 | - Face Benchmark&Dataset: face_benchmark-and-dataset.md 66 | - Face Lib&Tool: face_lib-and-tool.md 67 | - About: about.md 68 | # - Release Notes: about/release-notes.md 69 | # - Contributing: about/contributing.md 70 | # - License: about/license.md -------------------------------------------------------------------------------- /mkdocs.yml: -------------------------------------------------------------------------------- 1 | site_name: Hello Face 2 | site_url: https://becauseofAI.github.io/HelloFace 3 | site_description: Face Technology Repository. 4 | site_author: becauseofAI 5 | 6 | repo_url: https://github.com/becauseofAI/HelloFace 7 | edit_uri: "" 8 | repo_name: 'HelloFace' 9 | 10 | theme: 11 | name: material 12 | palette: 13 | primary: 'Indigo' 14 | accent: 'Pink' 15 | feature: 16 | tabs: false 17 | #font: 18 | #text: 'Ubuntu' 19 | #code: 'Ubuntu Mono' 20 | language: 'zh' 21 | 22 | extra: 23 | social: 24 | - type: github 25 | link: https://github.com/becauseofAI 26 | search: 27 | language: 'ja' 28 | 29 | markdown_extensions: 30 | - admonition 31 | - codehilite: 32 | guess_lang: false 33 | linenums: false 34 | - toc: 35 | permalink: true 36 | - footnotes 37 | - meta 38 | - def_list 39 | - pymdownx.arithmatex 40 | - pymdownx.betterem: 41 | smart_enable: all 42 | - pymdownx.caret 43 | - pymdownx.critic 44 | - pymdownx.details 45 | - pymdownx.emoji: 46 | emoji_generator: !!python/name:pymdownx.emoji.to_png 47 | #emoji_generator: !!python/name:pymdownx.emoji.to_svg 48 | #emoji_generator: !!python/name:pymdownx.emoji.to_png_sprite 49 | #emoji_generator: !!python/name:pymdownx.emoji.to_svg_sprite 50 | #emoji_generator: !!python/name:pymdownx.emoji.to_awesome 51 | #emoji_generator: !!python/name:pymdownx.emoji.to_alt 52 | - pymdownx.inlinehilite 53 | - pymdownx.magiclink 54 | - pymdownx.mark 55 | - pymdownx.smartsymbols 56 | - pymdownx.superfences 57 | - pymdownx.tasklist 58 | - pymdownx.tilde 59 | 60 | extra_javascript: 61 | - './js/extra.js' 62 | - './js/baidu-tongji.js' 63 | - 'https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-MML-AM_CHTML' 64 | 65 | extra_css: 66 | - './css/extra.css' 67 | 68 | copyright: Copyright © 2019 becauseofAI, Maintained by the becauseofAI. 69 | google_analytics: ['UA-27795084-5', 'mkdocs.org'] 70 | 71 | plugins: 72 | - search 73 | # - mknotebooks: 74 | # execute: false 75 | # preamble: "pandas_to_markdown.py" 76 | 77 | nav: 78 | - AllInOne: index.md 79 | - Face Recognition: face_recognition.md 80 | - Face Detection: face_detection.md 81 | - Face Landmark: face_landmark.md 82 | - Face Clustering: face_clustering.md 83 | - Face Expression: face_expression.md 84 | - Face Action: face_action.md 85 | - Face 3D: face_3d.md 86 | - Face GAN: face_gan.md 87 | - Face Manipulation: face_manipulation.md 88 | - Face Anti-Spoofing: face_anti-spoofing.md 89 | - Face Adversarial Attack: face_adversarial-attack.md 90 | - Face Cross-Modal: face_cross-modal.md 91 | - Face Capture: face_capture.md 92 | - Face Benchmark&Dataset: face_benchmark-and-dataset.md 93 | - Face Lib&Tool: face_lib-and-tool.md 94 | - About: about.md 95 | # - Release Notes: about/release-notes.md 96 | # - Contributing: about/contributing.md 97 | # - License: about/license.md -------------------------------------------------------------------------------- /site/404.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | Hello Face 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 97 | 98 | 99 | 100 | 101 | 102 | 103 | 104 | 105 | 106 | 107 | 108 | 109 | 110 | 111 | 112 | 113 | 114 | 115 | 116 | 117 | 118 | 119 | 120 |
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is ja je kan kon kunnen maar me meer men met mij mijn moet na naar niet niets nog nu of om omdat onder ons ook op over reeds te tegen toch toen tot u uit uw van veel voor want waren was wat werd wezen wie wil worden wordt zal ze zelf zich zij zijn zo zonder zou".split(" ")),e.Pipeline.registerFunction(e.du.stopWordFilter,"stopWordFilter-du")}}); -------------------------------------------------------------------------------- /site/assets/javascripts/lunr/lunr.es.js: -------------------------------------------------------------------------------- 1 | !function(e,s){"function"==typeof define&&define.amd?define(s):"object"==typeof exports?module.exports=s():s()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. 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noihin noiksi noilla noille noilta noin noina noissa noista noita nuo nyt näiden näihin näiksi näille näillä näiltä näinä näissä näistä näitä nämä ole olemme olen olet olette oli olimme olin olisi olisimme olisin olisit olisitte olisivat olit olitte olivat olla olleet ollut on ovat poikki se sekä sen siihen siinä siitä siksi sille sillä sillä siltä sinua sinulla sinulle sinulta sinun sinussa sinusta sinut sinuun sinä sinä sitä tai te teidän teidät teihin teille teillä teiltä teissä teistä teitä tuo tuohon tuoksi tuolla tuolle tuolta tuon tuona tuossa tuosta tuota tähän täksi tälle tällä tältä tämä tämän tänä tässä tästä tätä vaan vai vaikka yli".split(" ")),i.Pipeline.registerFunction(i.fi.stopWordFilter,"stopWordFilter-fi")}}); -------------------------------------------------------------------------------- /site/assets/javascripts/lunr/lunr.fr.js: -------------------------------------------------------------------------------- 1 | !function(e,r){"function"==typeof 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avute avuti avuto c che chi ci coi col come con contro cui da dagl dagli dai dal dall dalla dalle dallo degl degli dei del dell della delle dello di dov dove e ebbe ebbero ebbi ed era erano eravamo eravate eri ero essendo faccia facciamo facciano facciate faccio facemmo facendo facesse facessero facessi facessimo faceste facesti faceva facevamo facevano facevate facevi facevo fai fanno farai faranno farebbe farebbero farei faremmo faremo fareste faresti farete farà farò fece fecero feci fosse fossero fossi fossimo foste fosti fu fui fummo furono gli ha hai hanno ho i il in io l la le lei li lo loro lui ma mi mia mie miei mio ne negl negli nei nel nell nella nelle nello noi non nostra nostre nostri nostro o per perché più quale quanta quante quanti quanto quella quelle quelli quello questa queste questi questo sarai saranno sarebbe sarebbero sarei saremmo saremo sareste saresti sarete sarà sarò se sei si sia siamo siano siate siete sono sta stai stando stanno starai staranno starebbe 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-------------------------------------------------------------------------------- /site/assets/javascripts/lunr/lunr.no.js: -------------------------------------------------------------------------------- 1 | !function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. 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Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. 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către da dacă dar datorită dată dau de deci deja deoarece departe deşi din dinaintea dintr- dintre doi doilea două drept după dă ea ei el ele eram este eu eşti face fata fi fie fiecare fii fim fiu fiţi frumos fără graţie halbă iar ieri la le li lor lui lângă lîngă mai mea mei mele mereu meu mi mie mine mult multă mulţi mulţumesc mâine mîine mă ne nevoie nici nicăieri nimeni nimeri nimic nişte noastre noastră noi noroc nostru nouă noştri nu opt ori oricare orice oricine oricum oricând oricât oricînd oricît oriunde patra patru patrulea pe pentru peste pic poate pot prea prima primul prin puţin puţina puţină până pînă rog sa sale sau se spate spre sub sunt suntem sunteţi sută sînt sîntem sînteţi să săi său ta tale te timp tine toate toată tot totuşi toţi trei treia treilea tu tăi tău un una unde undeva unei uneia unele uneori unii unor unora unu unui unuia unul vi voastre voastră voi vostru vouă voştri vreme vreo vreun vă zece zero zi zice îi îl îmi împotriva în înainte înaintea încotro 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Please include / require Lunr before this script.");if(void 0===t.stemmerSupport)throw new Error("Lunr stemmer support is not present. 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r,i,e=L.limit-L.cursor;if(L.ket=L.cursor,!(I()||(L.cursor=L.limit-e,A()&&L.in_grouping_b(P,105,305)&&Z()||(L.cursor=L.limit-e,A()&&L.find_among_b(u,2)&&Z()))))return!1;if(L.bra=L.cursor,L.slice_del(),L.ket=L.cursor,r=L.limit-L.cursor,B())L.bra=L.cursor,L.slice_del(),i=L.limit-L.cursor,L.ket=L.cursor,Q()||(L.cursor=L.limit-i);else if(L.cursor=L.limit-r,!Q())return!0;return L.bra=L.cursor,L.slice_del(),L.ket=L.cursor,er(),!0}function sr(){var r,i,e=L.limit-L.cursor;if(L.ket=L.cursor,Q())return L.bra=L.cursor,L.slice_del(),void er();if(L.cursor=L.limit-e,L.ket=L.cursor,A()&&L.find_among_b(d,2)&&T())if(L.bra=L.cursor,L.slice_del(),r=L.limit-L.cursor,L.ket=L.cursor,G())L.bra=L.cursor,L.slice_del();else{if(L.cursor=L.limit-r,L.ket=L.cursor,!B()&&(L.cursor=L.limit-r,!D())){if(L.cursor=L.limit-r,L.ket=L.cursor,!Q())return;if(L.bra=L.cursor,L.slice_del(),!er())return}L.bra=L.cursor,L.slice_del(),L.ket=L.cursor,Q()&&(L.bra=L.cursor,L.slice_del(),er())}else 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r,i=L.cursor,e=2;;){for(r=L.cursor;!L.in_grouping(C,97,305);){if(L.cursor>=L.limit)return L.cursor=r,!(0 2 | 3 | 4 | https://becauseofAI.github.io/HelloFace/ 5 | 2019-08-16 6 | daily 7 | 8 | 9 | https://becauseofAI.github.io/HelloFace/face_recognition/ 10 | 2019-08-16 11 | daily 12 | 13 | 14 | https://becauseofAI.github.io/HelloFace/face_detection/ 15 | 2019-08-16 16 | daily 17 | 18 | 19 | https://becauseofAI.github.io/HelloFace/face_landmark/ 20 | 2019-08-16 21 | daily 22 | 23 | 24 | https://becauseofAI.github.io/HelloFace/face_clustering/ 25 | 2019-08-16 26 | daily 27 | 28 | 29 | https://becauseofAI.github.io/HelloFace/face_expression/ 30 | 2019-08-16 31 | daily 32 | 33 | 34 | https://becauseofAI.github.io/HelloFace/face_action/ 35 | 2019-08-16 36 | daily 37 | 38 | 39 | https://becauseofAI.github.io/HelloFace/face_3d/ 40 | 2019-08-16 41 | daily 42 | 43 | 44 | https://becauseofAI.github.io/HelloFace/face_gan/ 45 | 2019-08-16 46 | daily 47 | 48 | 49 | https://becauseofAI.github.io/HelloFace/face_manipulation/ 50 | 2019-08-16 51 | daily 52 | 53 | 54 | https://becauseofAI.github.io/HelloFace/face_anti-spoofing/ 55 | 2019-08-16 56 | daily 57 | 58 | 59 | https://becauseofAI.github.io/HelloFace/face_adversarial-attack/ 60 | 2019-08-16 61 | daily 62 | 63 | 64 | https://becauseofAI.github.io/HelloFace/face_cross-modal/ 65 | 2019-08-16 66 | daily 67 | 68 | 69 | https://becauseofAI.github.io/HelloFace/face_capture/ 70 | 2019-08-16 71 | daily 72 | 73 | 74 | https://becauseofAI.github.io/HelloFace/face_benchmark-and-dataset/ 75 | 2019-08-16 76 | daily 77 | 78 | 79 | https://becauseofAI.github.io/HelloFace/face_lib-and-tool/ 80 | 2019-08-16 81 | daily 82 | 83 | 84 | https://becauseofAI.github.io/HelloFace/about/ 85 | 2019-08-16 86 | daily 87 | 88 | -------------------------------------------------------------------------------- /site/sitemap.xml.gz: -------------------------------------------------------------------------------- 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