Abstract 3D face recognition has become a trending research direction in both industry and
academia. It inherits advantages from traditional 2D face recognition, such as the natural …

Deep learning, in particular the deep convolutional neural networks, has received
increasing interests in face recognition recently, and a number of deep learning methods …

Embedding methods have achieved success in face recognition by comparing facial
features in a latent semantic space. However, in a fully unconstrained face setting, the facial …

This paper presents a Neural Aggregation Network (NAN) for video face recognition. The
network takes a face video or face image set of a person with a variable number of face …

Generative 3D face models are a powerful tool in computer vision. They provide pose and
illumination invariance by modeling the space of 3D faces and the imaging process. The …

Deep face recognition has achieved remarkable improvements due to the introduction of
margin-based softmax loss, in which the prototype stored in the last linear layer represents …

We propose a novel discriminative learning approach to image set classification by
modeling the image set with its natural second-order statistic, ie covariance matrix. Since …

In the traditional distributed machine learning scenario, the user's private data is transmitted
between clients and a central server, which results in significant potential privacy risks. In …

Abstract The manifold of Symmetric Positive Definite (SPD) matrices has been successfully
used for data representation in image set classification. By endowing the SPD manifold with …

In computer vision, we generally solve a classification problem by a single image. With the
video cameras being widely used in our real life, it is a nature choice to solve a classification …