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 …

Human pose estimation aims to locate the human body parts and build human body
representation (eg, body skeleton) from input data such as images and videos. It has drawn …

Human skeleton, as a compact representation of human action, has received increasing
attention in recent years. Many skeleton-based action recognition methods adopt GCNs to …

In action recognition, although the combination of spatio-temporal videos and skeleton
features can improve the recognition performance, a separate model and balancing feature …

Multimodal action recognition techniques combine several image modalities (RGB, Depth,
Skeleton, and InfraRed) for a more robust recognition. According to the fusion level in the …

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 …

Human–robot collaborative assembly (HRCA) is vital for achieving high-level flexible
automation for mass personalization in today's smart factories. However, existing works in …

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 …

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 …

Abstract 3D human pose estimation (3D HPE) in autonomous vehicles (AV) differs from
other use cases in many factors, including the 3D resolution and range of data, absence of …