迄今最全人脸识别开源 - qq_34654240的博客 - CSDN博客
人脸识别是目前深度学习领域应用最为广泛的领域之一,各大框架都有不错的开源项目,可以在短时间内实现刷榜。
首推 Demystifying Face Recognition,由浅入深实验了很多方法
如何走近深度学习人脸识别: https://github.com/Joker316701882/Additive-Margin-Softmax
caffe
https://github.com/wy1iu/sphereface:lfw 99.30% with A-softmax loss 中文理解
https://github.com/happynear/NormFace:99.21%
https://github.com/ydwen/caffe-face:~99% centerloss,ECCV2016
https://github.com/AlfredXiangWu/face_verification_experiment98.80% with CASIA,Light-CNN
mxnet
https://github.com/deepinsight/insightface:lfw 99.83%
https://github.com/moli232777144/mobilefacenet-mxnet:轻量级版本99.5%
https://github.com/qidiso/mobilefacenet-V2:99.66%
tensorflow
https://github.com/davidsandberg/facenet:lfw 99.65%
多GPU版本: https://github.com/wangruichens/facenet_multigpu
https://github.com/auroua/InsightFace_TF:99.68%
https://github.com/xsr-ai/MobileFaceNet_TF
人脸对齐
https://github.com/CamlinZ/face_alignment一种人脸68特征点检测的深度学习方法
https://github.com/zeusees/HyperLandmark106点标注,含android端
https://github.com/tensor-yu/cascaded_mobilenet-v2: 级联MobileNet-V2进行人脸关键点(5点)检测,单模型仅 956 KB,GTX1080上运行为6ms左右
https://github.com/goodluckcwl/Face-alignment-mobilenet-v2
Loss Function
https://github.com/KaleidoZhouYN/Loss-Functions
https://github.com/KaleidoZhouYN/Sphereface-Ms-celeb-1M:讨论对齐的影响
商业实践
InsightFace - 使用篇, 如何一键刷分LFW 99.80%, MegaFace 98%
facenet 代码阅读笔记:如何训练基于triplet-loss的模型
https://github.com/seetaface/SeetaFaceEngine:山世光老师的开源库,不过有点过时了
A-Softmax的总结及与L-Softmax的对比——SphereFace
A Discriminative Feature Learning Approach for Deep Face Recognition 原理及在caffe实验复现
android
https://github.com/GRAYKEY/mobilefacenet_android
https://github.com/zhanglaplace/MobileFaceNetAmsoftmax实现
https://github.com/KaleidoZhouYN/mobilefacenet-caffe:
https://github.com/moli232777144/small_model_face_recognition:Light CNN for ncnn
https://github.com/mohanson/FaceDetectionServer:go服务器人脸识别服务
https://github.com/yanmeizhao/Sara/tree/master/sample_mobile_track_106:商汤106点人脸跟踪
数据集
MS1M
VGGFace2
--------------------- 本文来自 迷若烟雨 的CSDN 博客 ,全文地址请点击:https://blog.csdn.net/minstyrain/article/details/82292278?utm_source=copy