Understanding of ArcLoss in 《ArcFace -Additive Angular Margin Loss for Deep Face Recognition》

• Introduction
  Here is some understanding of ArcLoss in <ArcFace: Additive Angular Margin Loss for Deep Face Recognition> ArcFace ’ main contribution is training a DCNN model with ArcFace Loss. In face recognition task, firstly train a DCNN with loss function. The common way for doing that is in using Softmax loss function, which declared below:

• Softmax

  • formula (1):
    
    Our goal is to minimise L1, so the more L1 approaches to 0, the better the model is. We notice the formula, when L1 equals to 0, means log(X) equals to 0 so that X should more approach to 1. And only if e^(W_yi xi + b_yi)^ is maxed enough, the whole part of X will equal to 1.
    So during the training procession, the weights W will convergence to a matrix to make xi multiply W_yi large enough.
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