Knot Magnify Loss for Face Recognition

@article{Rao2018KnotML,
  title={Knot Magnify Loss for Face Recognition},
  author={Qiang Rao and Bing Yu and Yun Yang and Bailan Feng},
  journal={2018 25th IEEE International Conference on Image Processing (ICIP)},
  year={2018},
  pages={2396-2400}
}
  • Qiang Rao, Bing Yu, +1 author Bailan Feng
  • Published in
    25th IEEE International…
    2018
  • Computer Science
  • Deep Convolutional Neural Netowrks (DCNN) have significantly improved the performance of face recognition in recent years. Softmax loss is the most widely used loss function for training the DCNN-based face recognition system. It gives the same weights to easy and hard samples in one batch, which would leads to performance gap on the quality imbalanced data. In this paper, we discover that the rare hard samples in the training dataset has become a main obstacle for training a robust face… CONTINUE READING

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