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 …

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 …

Human activity recognition (HAR) has become a significant area of research in human
behavior analysis, human–computer interaction, and pervasive computing. Recently, deep …

Human-centric perceptions (eg, pose estimation, human parsing, pedestrian detection,
person re-identification, etc.) play a key role in industrial applications of visual models. While …

Skeleton-based action recognition has attracted lots of research attention. Recently to build
an accurate skeleton-based action recognizer a variety of works have been proposed …

Existing person re-identification methods have achieved remarkable advances in
appearance-based identity association across homogeneous cameras such as ground …

Human-centric perceptions include a variety of vision tasks, which have widespread
industrial applications, including surveillance, autonomous driving, and the metaverse. It is …

Abstract Large scale Vision-Language (VL) models have shown tremendous success in
aligning representations between visual and text modalities. This enables remarkable …

Skeleton-based human action recognition has attracted increasing attention in recent years.
However, most of the existing works focus on supervised learning which requiring a large …

The advancement of computer vision technology has led to the development of
sophisticated algorithms capable of accurately recognizing human actions from red-green …