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face-retrive-recognition-system

亚洲人脸检索识别模型，支持人脸识别，人脸检索，支持各种平台，总模型大小9MB，ios、android、 pc(linux、windows、mac)总共(检测、对齐、特征计算)运行40ms，库独立，完全没有第三方库，方便部署，facial recognition system. android,ios , linux ,windows, mac and so on.model size is 9MB,very fast

face-track-detect-extract

💎 Detect , track and extract the optimal face in multi-target faces (exclude side face and select the optimal face).

face-tracker

Face Tracker using RetinaFace Detector and Kalman Filter

face-tracking-based-on-opentld-and-rnet

I optimized OpenTLD making it run faster and better for face tracking.

face.evolve.pytorch

🔥🔥High-Performance Face Recognition Library on PyTorch🔥🔥

face.ncnn

基于 ncnn 框架搭建 win 及 android 端的人脸检测工程

face2facetranslator

面对面翻译小程序是微信团队针对面对面沟通的场景开发的流式语音翻译小程序，通过微信同声传译插件提供了语音识别，文本翻译等功能。

faceaging-by-cyclegan

faceapp

Facial analysis for expression recognition

faceattribute-fan

faceboxes

FaceBoxes: A CPU Real-time Face Detector with High Accuracy

faceboxes-1

FaceBoxes: A CPU Real-time Face Detector with High Accuracy

faceboxes-2

FaceBoxes: A CPU Real-time Face Detector with High Accuracy, IJCB, 2017

facecapture

an Android app kind like Facerig(but simpler)

facecomparison

This project include face-deteciton face-landmarks face-align and face-recgnition; It is a relatively complete project！

facedemo

A demo of real-time face recognition on Android.

facedetect-facelandmark

基于ncnn的手机端轻量级人脸检测和关键点定位模型

facedetect-ios

fast face detect

facedetectandtracking

基于多人脸检测和跟踪的行人统计

facedetection

人脸识别合集

facedetection-dsfd

facedetection_cnn

Multi-view Face Detection Using Deep Convolutional Neural Networks

facedetection_system-

1.face_detector(Seetaface)2.add face_tracking 3.add sleep/wake-up 4.use c++ boost filesystem

facedetectionserver

基于 SeetaFace 的人脸识别服务, By and For Golang

facefrontalization

Align a face in profile to front view

facejni

Face Api for Detection and Recognition with multi-context support on Caffe.

facelandmark1000

1000点的人脸关键点检测

faceliveness

Face Liveness Detection 静默型的人脸活体检测项目

faceliveness-1

人脸识别，face++再打包

facemask-recognition

此一project是由清华大学医学院的姚非凡与郑家瀚共同开发完成，这里运用了三个目标检测模型，来找到图像里的人脸，以及他们是否有带口罩，是个目标检测+2分类问题。 这一readme.md文件是为了帮助使用者如何正确使用我们的code。我们使用FasterRCNN可达到0.7的mAP[.5:.95]。