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Set a bigger margin parameter (0.35) and a higher feature embedding demension (1024)
Use the clean dataset and the details can be seen this
CosFace
This project is aimmed at implementing the CosFace described by the paper CosFace: Large Margin Cosine Loss for Deep Face Recognition. The code can be trained on CASIA-Webface and the best accuracy LFW is 98.6%. The result is lower than reported by paper(99.33%), which may be caused by sphere network implemented in tensorflow. I train the sphere network implemented in tensorflow using the softmax loss and just obtain the accuracy 95.6%, which is more lower than caffe version(97.88%).
Preprocessing
I supply the preprocessed dataset in baidu pan:CASIA-WebFace-112X96,lfw-112X96. You can download and unzip them to dir dataset.
If you want to preprocess the dataset by yourself, you can refer to sphereface.
Train
./train.sh
Test
Modify the MODEL_DIR in test.sh and run ./test.sh.
If you do not want to train your model, you can download my trained model and unzip it to models dir.