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Face_Recognition

Chapter5 - Homework - loss_function&Deep_Metric_Learning - shenlanxueyuan

Dataset find it in GITHUB Share

CASIAWebFace:

(https://drive.google.com/file/d/1wJC2aPA4AC0rI-tAL2BFs2M8vfcpX-w6/view?usp=sharing)

unzip casia-maxpy-clean.zip

cd casia-maxpy-clean

zip -F CASIA-maxpy-clean.zip --out CASIA-maxpy-clean_fix.zip

unzip CASIA-maxpy-clean_fix.zip

LFW:

(https://pan.baidu.com/s/1Rue4FBmGvdGMPkyy2ZqcdQ)

Homework Result

SEResNet18 Best acc on LFW SEResNet34 Best acc on LFW
Softmax 0.851 Softmax 0.8578333333333333
NormFace 0.8428333333333334 NormFace 0.8470000000000001
SpereFace 0.8474999999999999 SpereFace 0.8651666666666665
CosFace 0.8488333333333333 CosFace 0.8504999999999999
ArcFace 0.8456666666666667 ArcFace 0.755
OHEM & NormFace 0.8456666666666667 OHEM & NormFace 0.8485000000000001
FocalLoss & NormFace 0.8396666666666667 FocalLoss & NormFace 0.8504999999999999

Notes: Train from scratch and run 20 epochs @ Tesla P100 16G; SEResNet18 @ 20epoch、batchsize=256; SEResNet34 @20epoch、batchsize=128

SEResNet18 Best acc on LFW SEResNet34 Best acc on LFW
Contrastive(Scratch) 0.6135(20epoch、batchsize=128) Contrastive(Scratch) \
Triplet(Scratch) 0.7968(4epoch、batchsize=64) Triplet(Scratch) 0.8265(4epoch、batchsize=256、Quadro RTX8000 48G)
Contrastive(Finetune) 0.6371666666666667(20epoch、batchsize=128) Contrastive(Finetune) \
Triplet(Finetune) \ Triplet(Finetune) \

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