Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …

Abstract Human Action Recognition (HAR) involves human activity monitoring task in
different areas of medical, education, entertainment, visual surveillance, video retrieval, as …

Anomaly detection in videos remains a challenging task due to the ambiguous definition of
anomaly and the complexity of visual scenes from real video data. Different from the …

Recent advances in Internet of Things (IoT) technologies and the reduction in the cost of
sensors have encouraged the development of smart environments, such as smart homes …

In this paper, we focus on the spatio-temporal aspect of recognizing Activities of Daily Living
(ADL). ADL have two specific properties (i) subtle spatio-temporal patterns and (ii) similar …

Human action recognition (HAR) in RGB-D videos has been widely investigated since the
release of affordable depth sensors. Currently, unimodal approaches (eg, skeleton-based …

In this work, we present a method for RGB-based action recognition using multi-view videos.
We present a supervised contrastive learning framework to learn a feature embedding …

Graph convolution networks (GCN) have been widely used in skeleton-based action
recognition. We note that existing GCN-based approaches primarily rely on prescribed …

Classification of human actions is an ongoing research problem in computer vision. This
review is aimed to scope current literature on data fusion and action recognition techniques …

Many attempts have been made towards combining RGB and 3D poses for the recognition
of Activities of Daily Living (ADL). ADL may look very similar and often necessitate to model …