Image-set classification has recently generated great popularity due to its widespread
applications in computer vision. The great challenges arise from effectively and efficiently …

Image set classification, which compares the similarity between image sets with variable
quantity, quality and unordered heterogeneous images, has drawn increased research …

With the rapid advances in digital imaging and communication technologies, recently image
set classification has attracted significant attention and has been widely used in many real …

In this paper, we investigate the problem of classifying an image set of an object, and
develop a novel image set representation and classification algorithm. We propose to …

This paper presents a new approach for image set classification, where each training and
testing example contains a set of image instances of an object captured from varying …

In this paper, we propose a multi-manifold deep metric learning (MMDML) method for image
set classification, which aims to recognize an object of interest from a set of image instances …

Existing multi-model approaches for image set classification extract local models by
clustering each image set individually only once, with fixed clusters used for matching with …

Image set classification has attracted much attention because of its broad applications.
Despite the success made so far, the problems of intra-class diversity and inter-class …

Image set classification has recently attracted great attention due to its widespread
applications in computer vision and pattern recognition. The great challenges lie in …

This paper targets on the problem of set to set recognition, which learns the metric between
two image sets. Images in each set belong to the same identity. Since images in a set can be …