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https://github.com/coderonion/awesome-face-detection-and-recognition

A collection of some awesome public face detection and recognition projects.
https://github.com/coderonion/awesome-face-detection-and-recognition

List: awesome-face-detection-and-recognition

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A collection of some awesome public face detection and recognition projects.

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# Awesome-Face-Detection-and-Recognition
[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)

🔥🔥🔥 This repository lists some awesome face detection and recognition projects.

## Contents
- [Awesome-Face-Detection-and-Recognition](#awesome-face-detection-and-recognition)
- [Summary](#summary)
- [Face Detection](#face-detection)
- [Face Recognition](#face-recognition)
- [Datasets](#datasets)
- [Face Detection Datasets](#face-detection-datasets)
- [Face Recognition Datasets](#face-recognition-datasets)

## Summary

- [ChanChiChoi/awesome-Face_Recognition](https://github.com/ChanChiChoi/awesome-Face_Recognition) : papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval.

- [becauseofAI/awesome-face](https://github.com/becauseofAI/awesome-face) : An awesome face technology repository.

- [ageitgey/face_recognition](https://github.com/ageitgey/face_recognition) : The world's simplest facial recognition api for Python and the command line.

- [takuya-takeuchi/FaceRecognitionDotNet](https://github.com/takuya-takeuchi/FaceRecognitionDotNet) : The world's simplest facial recognition api for .NET on Windows, MacOS and Linux.

- [polarisZhao/awesome-face](https://github.com/polarisZhao/awesome-face) : 😎 face releated algorithm, dataset and paper.

- [clpeng/Awesome-Face-Forgery-Generation-and-Detectione](https://github.com/clpeng/Awesome-Face-Forgery-Generation-and-Detectione) : A curated list of articles and codes related to face forgery generation and detection.

## Face Detection

- Viola-Jones : "Robust Real-Time Face Detection". (**[IJCV 2004](https://link.springer.com/article/10.1023/B:VISI.0000013087.49260.fb)**)

- [MTCNN](https://github.com/kpzhang93/MTCNN_face_detection_alignment) : "Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks". (**[IEEE signal processing letters, 2016](https://ieeexplore.ieee.org/abstract/document/7553523/)**)

- [FaceBoxes](https://github.com/sfzhang15/FaceBoxes) : "FaceBoxes: A CPU real-time face detector with high accuracy". (**[IJCB, 2017](https://ieeexplore.ieee.org/abstract/document/8272675)**)

- [DSFD](https://github.com/Tencent/FaceDetection-DSFD) : "DSFD: Dual Shot Face Detector". (**[CVPR 2019](https://openaccess.thecvf.com/content_CVPR_2019/html/Li_DSFD_Dual_Shot_Face_Detector_CVPR_2019_paper.html)**)

- [RetinaFace](https://github.com/biubug6/Pytorch_Retinaface) : "RetinaFace: Single-Shot Multi-Level Face Localisation in the Wild". (**[CVPR 2020](https://openaccess.thecvf.com/content_CVPR_2020/html/Deng_RetinaFace_Single-Shot_Multi-Level_Face_Localisation_in_the_Wild_CVPR_2020_paper.html)**)

- [hukkelas/DSFD-Pytorch-Inference](https://github.com/hukkelas/DSFD-Pytorch-Inference) : State of the Art Face Detection in Pytorch with DSFD and RetinaFace.

- [SCRFD](https://github.com/deepinsight/insightface/tree/master/detection/scrfd) : "Sample and Computation Redistribution for Efficient Face Detection". (**[arXiv 2021](https://arxiv.org/abs/2105.04714)**)

- [YOLO5Face](https://github.com/deepcam-cn/yolov5-face) : "YOLO5Face: Why Reinventing a Face Detector". (**[arXiv 2021](https://arxiv.org/abs/2105.12931)**)

- [YOLO-FaceV2](https://github.com/Krasjet-Yu/YOLO-FaceV2) : "YOLO-FaceV2: A Scale and Occlusion Aware Face Detector ". (**[arXiv 2022](https://arxiv.org/abs/2208.02019)**). "微信公众号「江大白」《[超越Yolo5-Face,Yolo-Facev2开源,各类Trick优化,值得学习!](https://mp.weixin.qq.com/s?__biz=Mzg5NzgyNTU2Mg==&mid=2247498561&idx=1&sn=b7ff0592644ab6bc5b716e07294e1c0a&source=41#wechat_redirect)》"

- [OAID/TengineKit](https://github.com/OAID/TengineKit) : TengineKit - Free, Fast, Easy, Real-Time Face Detection & Face Landmarks & Face Attributes & Hand Detection & Hand Landmarks & Body Detection & Body Landmarks & Iris Landmarks & Yolov5 SDK On Mobile.

- [xialuxi/yolov5_face_landmark](https://github.com/xialuxi/yolov5_face_landmark) : 基于yolov5的人脸检测,带关键点检测。

- [sthanhng/yoloface](https://github.com/sthanhng/yoloface) : Deep learning-based Face detection using the YOLOv3 algorithm.

- [DayBreak-u/yolo-face-with-landmark](https://github.com/DayBreak-u/yolo-face-with-landmark) : yoloface大礼包 使用pytroch实现的基于yolov3的轻量级人脸检测(包含关键点)。

- [abars/YoloKerasFaceDetection](https://github.com/abars/YoloKerasFaceDetection) : Face Detection and Gender and Age Classification using Keras.

- [dannyblueliu/YOLO-Face-detection](https://github.com/dannyblueliu/YOLO-Face-detection) : Face detection based on YOLO darknet.

- [wmylxmj/YOLO-V3-IOU](https://github.com/wmylxmj/YOLO-V3-IOU) : YOLO3 动漫人脸检测 (Based on keras and tensorflow) 2019-1-19.

- [pranoyr/head-detection-using-yolo](https://github.com/pranoyr/head-detection-using-yolo) : Detection of head using YOLO.

- [grapeot/AnimeHeadDetector](https://github.com/grapeot/AnimeHeadDetector) : An object detector for character heads in animes, based on Yolo V3.

- [Chenyang-ZHU/YOLOv3-Based-Face-Detection-Tracking](https://github.com/Chenyang-ZHU/YOLOv3-Based-Face-Detection-Tracking) : This is a robot project for television live. System will tracking the host's face, making the face in the middle of the screen.

- [zdfb/Yolov5_face](https://github.com/zdfb/Yolov5_face) : 基于pytorch的Yolov5人脸检测。

- [derronqi/yolov7-face](https://github.com/derronqi/yolov7-face) : yolov7 face detection with landmark.

## Face Recognition

- [DeepFace] : "DeepFace: Closing the Gap to Human-Level Performance in Face Verification". (**[CVPR 2014](https://openaccess.thecvf.com/content_cvpr_2014/html/Taigman_DeepFace_Closing_the_2014_CVPR_paper.html)**)

- [DeepID2]: "FaceNet: A Unified Embedding for Face Recognition and Clustering". (**[NIPS 2014](https://proceedings.neurips.cc/paper/2014/hash/e5e63da79fcd2bebbd7cb8bf1c1d0274-Abstract.html)**)

- [VGGFace](https://www.robots.ox.ac.uk/~vgg/software/vgg_face/): "Deep Face Recognition". (**[British Machine Vision Conference, 2015](https://www.robots.ox.ac.uk/~vgg/publications/2015/Parkhi15)**)

- [FaceNet](https://github.com/davidsandberg/facenet) : "Deep learning face representation by joint identification-verification". (**[CVPR 2015](https://www.cv-foundation.org/openaccess/content_cvpr_2015/html/Schroff_FaceNet_A_Unified_2015_CVPR_paper.html)**)

- [CosFace]: "CosFace: Large Margin Cosine Loss for Deep Face Recognition". (**[CVPR 2018](https://openaccess.thecvf.com/content_cvpr_2018/html/Wang_CosFace_Large_Margin_CVPR_2018_paper.html)**)

- [MobileFaceNets]: "MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices". (**[CCBR 2018](https://link.springer.com/chapter/10.1007/978-3-319-97909-0_46)**)

- [ArcFace](https://github.com/deepinsight/insightface) : State-of-the-art 2D and 3D Face Analysis Project. "Arcface: Additive angular margin loss for deep face recognition". (**[CVPR 2019](https://openaccess.thecvf.com/content_CVPR_2019/html/Deng_ArcFace_Additive_Angular_Margin_Loss_for_Deep_Face_Recognition_CVPR_2019_paper.html)**).

- [SphereFace](https://github.com/wy1iu/sphereface) : "SphereFace: Deep Hypersphere Embedding for Face Recognition". (**[CVPR 2017](https://openaccess.thecvf.com/content_cvpr_2017/html/Liu_SphereFace_Deep_Hypersphere_CVPR_2017_paper.html)**).

- [OpenSphere](https://github.com/ydwen/opensphere) : OpenSphere is a hyperspherical face recognition library based on PyTorch. "SphereFace: Deep Hypersphere Embedding for Face Recognition". (**[CVPR 2017](https://openaccess.thecvf.com/content_cvpr_2017/html/Liu_SphereFace_Deep_Hypersphere_CVPR_2017_paper.html)**). "SphereFace2: Binary Classification is All You Need for Deep Face Recognition". (**[ICLR 2022](https://wyliu.com/papers/sphereface2_ICLR22.pdf)**). "SphereFace Revived: Unifying Hyperspherical Face Recognition". (**[TPAMI 2022](https://wyliu.com/papers/spherefacer_v3_TPAMI.pdf)**).

- [ViewFaceCore/ViewFaceCore](https://github.com/ViewFaceCore/ViewFaceCore) : C# 超简单的离线人脸识别库。( 基于 SeetaFace6 )

- [serengil/deepface](https://github.com/serengil/deepface) : A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python.

- [ZhaoJ9014/face.evoLVe](https://github.com/ZhaoJ9014/face.evoLVe) : 🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥.

- [hpc203/10kinds-light-face-detector-align-recognition](https://github.com/hpc203/10kinds-light-face-detector-align-recognition) : 10种轻量级人脸检测算法的比拼,其中还包含人脸关键点检测与对齐,人脸特征向量提取和计算距离相似度。

- [coneypo/Dlib_face_recognition_from_camera](https://github.com/coneypo/Dlib_face_recognition_from_camera) : Detect and recognize the faces from camera / 调用摄像头进行人脸识别,支持多张人脸同时识别。

- [zhouyuchong/face-recognition-deepstream](https://github.com/zhouyuchong/face-recognition-deepstream) : Deepstream app use YOLO, retinaface and arcface for face recognition.

- [ColinFred/yolov5_arcface_face_recognition](https://github.com/ColinFred/yolov5_arcface_face_recognition) : 利用Yolov5做人脸检测,框出识别到的人脸,用 ArcFace 做人脸识别。 (**[Yolov5 + ArcFace 人脸识别](https://blog.csdn.net/windowsyun/article/details/123607549)**)

- [mesutpiskin/face-detection-and-recognition](https://github.com/mesutpiskin/face-detection-and-recognition) : C# Face detection and recognition with EmguCV. Eigenfaces, Fisherfaces and LBPH algorithms.

## Datasets

- ### Face Detection Datasets

- [WIDER FACE](http://shuoyang1213.me/WIDERFACE/) : "WIDER FACE: A Face Detection Benchmark". (**[CVPR 2016](https://openaccess.thecvf.com/content_cvpr_2016/html/Yang_WIDER_FACE_A_CVPR_2016_paper.html)**)

- [UFDD](https://ufdd.info/) : Unconstrained Face Detection Dataset(UFDD). "Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results". (**[IEEE BTAS 2018](https://ieeexplore.ieee.org/abstract/document/8698561l)**)

- ### Face Recognition Datasets

- [LFW](http://vis-www.cs.umass.edu/lfw/) : Labeled Faces in the Wild(LFW). "Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments". (**[Workshop on faces in'Real-Life'Images: detection, alignment, and recognition. 2008](https://hal.inria.fr/inria-00321923/)**)

- [YouTube Faces (YTF)](http://www.cs.tau.ac.il/~wolf/ytfaces/) : "Face recognition in unconstrained videos with matched background similarity". (**[CVPR 2011](https://ieeexplore.ieee.org/abstract/document/5995566)**)

- [CASIA-WebFace](https://pan.baidu.com/s/1k3Cel2wSHQxHO9NkNi3rkg) : "Learning Face Representation from Scratch". (**[arXiv 2014](https://arxiv.org/abs/1411.7923)**)

- [IJB-A](https://www.nist.gov/programs-projects/face-challenges) : "Pushing the Frontiers of Unconstrained Face Detection and Recognition: IARPA Janus Benchmark A". (**[CVPR 2015](https://www.cv-foundation.org/openaccess/content_cvpr_2015/html/Klare_Pushing_the_Frontiers_2015_CVPR_paper.html)**)

- [MS-Celeb-1M](https://academictorrents.com/details/9e67eb7cc23c9417f39778a8e06cca5e26196a97/tech&hit=1&filelist=1) : "MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition". (**[ECCV 2016](https://link.springer.com/chapter/10.1007/978-3-319-46487-9_6)**)

- [MegaFace](http://megaface.cs.washington.edu/) : "The MegaFace Benchmark: 1 Million Faces for Recognition at Scale". (**[CVPR 2016](https://openaccess.thecvf.com/content_cvpr_2016/html/Kemelmacher-Shlizerman_The_MegaFace_Benchmark_CVPR_2016_paper.html)**)

- [UMDFaces](https://www.umdfaces.io/) : "UMDFaces: An annotated face dataset for training deep networks". (**[IJCB 2017](https://ieeexplore.ieee.org/abstract/document/8272731)**)

- [IJB-B](https://www.nist.gov/programs-projects/face-challenges) : "IARPA Janus Benchmark-B Face Dataset". (**[CVPR 2017](https://openaccess.thecvf.com/content_cvpr_2017_workshops/w6/html/Whitelam_IARPA_Janus_Benchmark-B_CVPR_2017_paper.html)**)

- [IJB-C](https://www.nist.gov/programs-projects/face-challenges) : "IARPA Janus Benchmark - C: Face Dataset and Protocol". (**[ICB 2018](https://ieeexplore.ieee.org/abstract/document/8411217)**)

- [VGGFace2]() : "VGGFace2: A Dataset for Recognising Faces across Pose and Age". (**[FG 2018](https://ieeexplore.ieee.org/abstract/document/8373813)**)