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If trained with MS-Celeb-1M or VggFace2 dataset ,how much can the test result be improved? #2

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LingJiangXie opened this issue Jul 13, 2018 · 9 comments

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@LingJiangXie
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@MuggleWang
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I don't know because I have never done such an experiment. You can try it with a simple modification.

@gdshen
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gdshen commented Oct 18, 2018

I have trained on the msceleb cleaned by insightface, and have achieved 99.6~99.7 accuracy in LFW with resnet50.

@Sayyam-Jain
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I have trained on the msceleb cleaned by insightface, and have achieved 99.6~99.7 accuracy in LFW with resnet50.

Can you please share the model weights?

@akumar14
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akumar14 commented Mar 1, 2019

Can you also share the model on One Drive ?

@weihua04
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I have trained on the msceleb cleaned by insightface, and have achieved 99.6~99.7 accuracy in LFW with resnet50.
@gdshen i use the msceleb cleaned by insightface 、 LResnetE50-IR + cosFace ,but the entropy loss is 10.9 and didn't decline, 93%~94% accuracy in LFW , have u ever met this problem

@MuggleWang
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MuggleWang commented Mar 20, 2019

Trained on VggFace2 with Sphere20. Achieved 99.55% on LFW. (Note: Input is 112X112)

@HeshamAMH
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please MuggleWang when I test your model (net_sphere20_data_vggface2_acc_9955.pth), I obtained an error:

RuntimeError: Error(s) in loading state_dict for sphere:
size mismatch for fc.weight: copying a param with shape torch.Size([512, 25088]) from checkpoint, the shape in current model is torch.Size([512, 21504]).

Thanks in advance

@MuggleWang
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MuggleWang commented Sep 2, 2020

@Heshammm Check your input size (112x112), and accordingly the last fully connected layer in the model file layer.py should be self.fc = nn.Linear(512 * 7 * 7, 512). And if input size is 112x96, it should be self.fc = nn.Linear(512 * 7 * 6, 512). Further, in the inference(test) stage, match them with the model *.pth.

@HeshamAMH
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HeshamAMH commented Sep 2, 2020

Deeply thanks Dr. MuggleWang.

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