Journal: IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Programming languages: C, Cmake, Cuda, Jupyter Notebook, Matlab, Python
Project website: https://github.com/wy1iu/sphereface
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.