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What‘s the performance of AMSoftmax on larger datasets? MsCeleb, vggface2 #3

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SeuTao opened this issue Jan 25, 2018 · 5 comments

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@SeuTao
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SeuTao commented Jan 25, 2018

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@happynear
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Using vggface2, I can get better results on LFW, and a similar result on MegaFace.

Same with the order in the paper:
99.50% | 97.97% | 99.37% | 93.13%|72.78% | 86.29%

I haven't done experiments using MSCeleb-1m because I still haven't gotten the overlapped list between MSCeleb and LFW/FaceScrub.

@SeuTao
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SeuTao commented Jan 25, 2018

Thanks for sharing!I’ve tried your AMSoftmax using MsCeleb-1m on my own model. With the default
param setting (m0.35,s30) , I can get slightly better results than A_softmax. For large datasets with much more identities, do u have any advice for tuning the params(m&s) ?

@happynear
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If you have more identities, it is better to set a bigger s. I haven't done the experiment, but I guess 60 may be suitable for MSCeleb-1m.
The m is depending on the difficulty of the dataset. Now I have no idea about the best value for MSCeleb-1m. Maybe you can only search for it...

@SeuTao
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SeuTao commented Jan 25, 2018

Thanks again!!! I’ll try it.

@SeuTao SeuTao closed this as completed Jan 25, 2018
@liuruqin001
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train on MSCeleb-1m ,not pca, not delete overlapped on lfw 。
result: 0.238 ,0.99650000,0.00266667 , 0.00433333.
AMSoftmax is very good loss function,easier to train 。
@happynear Thanks for your good jobs!

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