Dictionary learning has became an increasingly important task in machine learning, as it is
fundamental to the representation problem. A number of emerging techniques specifically …

With the improved accessibility to an exploding amount of video data and growing demands
in a wide range of video analysis applications, video-based action recognition/classification …

In this paper, we propose an adaptive spatial pooling method for enhancing the
discriminability of feature representation for image classification. The core idea is to adopt a …

An increasing number of computer vision tasks can be tackled with deep features, which are
the intermediate outputs of a pre-trained Convolutional Neural Network. Despite the …

Image classification is a fundamental task in computer vision, implying a wide range of
challenging problems, such as object recognition, scene understanding, and image tagging …

Goal-driven top-down mechanism plays important role in the case of object detection and
recognition. In this paper, we propose a top-down computational model for goal-driven …

This paper presents a hierarchical and compositional scene layout (ie, spatial configuration)
representation and a method of learning reconfigurable model for scene categorization …

For image classification tasks, the region containing object which plays a decisive role is
indefinite in both position and scale. In this case, it does not seem quite appropriate to use …

In this paper, we present a “key segment” mining approach for human action recognition.
Our model is able to locate discriminative segments for action samples via multiple instance …

Recently, sparse coding-based algorithms have achieved high performance on several
popular scene classification benchmarks. Yet extensive efforts along this direction focus on …