Human face recognition have been an active research area for the last few decades.
Especially, during the last five years, it has gained significant research attention from …

Human activity recognition has been actively studied in the last three decades. Compared to
human action performed by a single person, human interaction is more complex due to the …

Person-person mutual action recognition (also referred to as interaction recognition) is an
important research branch of human activity analysis. Current solutions in the field–mainly …

Skeleton-based human interaction recognition is a challenging task requiring all abilities to
recognize spatial, temporal, and interactive features. These abilities rarely co-exist in …

Digitization of human motion using skeleton representations offers exciting possibilities for a
large number of applications but, at the same time, requires innovative techniques for their …

One of key challenges of skeleton-based action recognition (SAR) tasks is the complex
nature of human motion patterns. Variations such as performers and viewpoints may impose …

Research on group activity recognition mostly leans on the standard two-stream approach
(RGB and Optical Flow) as their input features. Few have explored explicit pose information …

Current researches of action recognition which focus on single-view and multi-view
recognition can hardly satisfy the requirements of human-robot interaction (HRI) applications …

Graph convolutional networks (GCNs) have been the predominant methods in skeleton-
based human action recognition, including human-human interaction recognition. However …

Recognizing interactions in multi-person videos known as Video Interaction Recognition
(VIR) is crucial for understanding video content. Often the human skeleton pose (skeleton for …