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# Variational Prototype Learning for Deep Face Recognition
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This is the Pytorch implementation of our paper [Variational Prototype Learning for Deep Face Recognition ](https://openaccess.thecvf.com/content/CVPR2021/papers/Deng_Variational_Prototype_Learning_for_Deep_Face_Recognition_CVPR_2021_paper.pdf ) which is accepted by CVPR-2021.
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## How to run
Define a new configure file such as `configs/example_ms1m.py` , and start the training process by:
``
bash run.sh configs/example_ms1m.py
``
## Results
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Results on WebFace600K(subset of WebFace260M), loss is margin-based softmax.
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| Backbone | Dataset | VPL? | Mask | Children | African | Caucasian | South Asian | East Asian | MR-All |
|------------|------------|------------|--------|----------|---------|-----------|-------------|------------|--------|
| R50 | WebFace600K | NO | 78.949 | 74.772 | 89.231 | 94.114 | 92.308 | 73.765 | 90.591 |
| R50 | WebFace600K | YES | 78.884 | 75.739 | 89.424 | 94.220 | 92.609 | 74.365 | 90.942 |
