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facerecognize-for-mobile-phone

适用于移动端的人脸识别模型，计算量于mobilefacenet相同，但megaface上提升了2%+。我训练的mobilefacenet在megaface VER上比原作者 高出了2%,因为训练的数据和方法不一样。

模型在各个数据集上表现如下：

Methods Flops (112x112) LFW CFP-FP AgeDB Megaface-Id Megaface-Ver@1e-6 备 注
MobileFaceNet440,R 440M 99.70+ 96.70+ 96.95+ 92.85+ 94.20+ 未开源
ZW350 356M 99.70+ 96.82+ 97.00+ 93.90+ 94.70+ 未开源
ZW400 404M 99.70+ 96.95+ 97.00+ 94.46+ 95.60+ 未开源
MobileFaceNet600,R 612M 99.76+ 97.60+ 97.50+ 95.14+ 95.98+ 已开源
ZW440 444M 99.76+ 97.30+ 97.40+ 95.25+ 96.00+ 已开源

Megafce测试结果图

zw440-id

模型地址

模型包含mxnet ncnn caffe 三种格式 BaiDu 提取码：b0dm

训练数据

https://github.com/deepinsight/insightface/tree/master/iccv19-challenge

参考项目

https://github.com/deepinsight/insightface

https://github.com/happynear/FaceVerification

https://github.com/Tencent/ncnn

Todo

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