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Face Recognition in PyTorch

This project mainly contains various loss function and light neural network.

Light Neural Network

  • MobileNet-v3
  • EfficientNet

    Loss function:

    These functions addresses deep face recognition (FR) problem under open-set protocol, where ideal face features are expected to have smaller maximal intra-class distance than minimal inter-class distance under a suitably chosen met- ric space.

  • Softmax:

  • CenterLoss:

  • L-Softmax:

    where

    Calculate phi(theta) and k:

    Calculate cos(m * theta):

  • Angular-Softmax:

  • Cosine-Softmax:

    where,

  • ArcFace:

    Reference

  • https://github.com/MuggleWang/CosFace_pytorch/blob/master/layer.py
  • ArcFace: Additive Angular Margin Loss for Deep Face Recognition
  • SphereFace: Deep Hypersphere Embedding for Face Recognition
  • A Discriminative Feature Learning Approach for Deep Face Recognition
  • CosFace: Large Margin Cosine Loss for Deep Face Recognition
  • Large-Margin Softmax Loss for Convolutional Neural Networks
  • EfficientNet
  • MobileNet-v3
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    Loss function, light neural network for face recognition.

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