SphereFace

Year: 2,017
Journal:  IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Programming languages: C, Cmake, Cuda, Jupyter Notebook, Matlab, Python

This paper 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 metric space. However, few existing algorithms can effectively achieve this criterion. To this end, we propose the angular softmax (A-Softmax) loss that enables convolutional neural networks (CNNs) to learn angularly discriminative features.

Sign In

Register

Reset Password

Please enter your username or email address, you will receive a link to create a new password via email.