Real world videos contain many complex actions with inherent relationships between action
classes. In this work, we propose an attention-based architecture that model these action …

In this paper, we propose a novel space-time geometric representation of human landmark
configurations and derive tools for comparison and classification. We model the temporal …

Rate of penetration (ROP) is a key metric used to monitor the success of drilling a well. It is
directly affected by drilling vibrations since excessive vibrations result in a reduction of ROP …

Vision Transformers are very popular nowadays due to their state-of-the-art performance in
several computer vision tasks, such as image classification and action recognition. Although …

In this paper, covariance matrices are exploited to encode the deep convolutional neural
networks (DCNN) features for facial expression recognition. The space geometry of the …

Emotion recognition is attracting great interest for its potential application in a multitude of
real-life situations. Much of the Computer Vision research in this field has focused on …

Gesture recognition is an imperative and practical problem owing to its great application
potential. Although recent works have made great progress in this field, there also exist three …

Recently, we combined a contour-detection network and a fully convolutional Siamese
tracking network to initialize a new start-up of vehicle tracking by clicking on the target …

Video action understanding involves comprehending actions performed by humans,
depicted in videos. Central to the task of video action understanding are four fundamental …

Developing intelligent systems dedicated to human behavior understanding has been a very
hot research topic in the few recent decades. Indeed, it is crucial to understand the human …