Jun Wang1, Suncheng Feng2,*, Yong Cheng3, Najla Al-Nabhan4
Journal of Information Hiding and Privacy Protection, Vol.3, No.1, pp. 29-45, 2021, DOI:10.32604/jihpp.2021.016835
- 21 April 2021
Abstract With the continuous development of face recognition network, the
selection of loss function plays an increasingly important role in improving
accuracy. The loss function of face recognition network needs to minimize the
intra-class distance while expanding the inter-class distance. So far, one of our
mainstream loss function optimization methods is to add penalty terms, such as
orthogonal loss, to further constrain the original loss function. The other is to
optimize using the loss based on angular/cosine margin. The last is Triplet loss
and a new type of joint optimization based on HST Loss and ACT More >
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