Three-dimensional skeleton-based action recognition (3D SAR) has gained important
attention within the computer vision community, owing to the inherent advantages offered by …

Skeleton-based action recognition has rapidly become one of the most popular and
essential research topics in computer vision. The task is to analyze the characteristics of …

Skeleton-based action recognition, which classifies human actions based on the
coordinates of joints and their connectivity within skeleton data, is widely utilized in various …

Higher-order interactions (HOIs) are ubiquitous in real-world complex systems and
applications. Investigation of deep learning for HOIs, thus, has become a valuable agenda …

The current 3D human pose estimators face challenges in adapting to new datasets due to
the scarcity of 2D-3D pose pairs in target domain training sets. We present the Multi …

Skeleton-based action recognition has garnered significant attention due to the utilization of
concise and resilient skeletons. Nevertheless, the absence of detailed body information in …

Human activity recognition (HAR) is an important research problem in computer vision. This
problem is widely applied to building applications in human–machine interactions …

In real-world scenarios, human actions often fall outside the distribution of training data,
making it crucial for models to recognize known actions and reject unknown ones. However …

Human pose estimation is a challenging task due to its structured data sequence nature.
Existing methods primarily focus on pair-wise interaction of body joints, which is insufficient …

Abstract Skeleton Action Recognition (SAR) has attracted significant interest for its efficient
representation of the human skeletal structure. Despite its advancements, recent studies …