Deep Learning is the most widely used tool in the contemporary field of computer vision. Its
ability to accurately solve complex problems is employed in vision research to learn deep …

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 …

Deep learning is at the heart of the current rise of artificial intelligence. In the field of
computer vision, it has become the workhorse for applications ranging from self-driving cars …

Contrastive learning has been successfully leveraged to learn action representations for
addressing the problem of semisupervised skeleton-based action recognition. However …

Over the recent years, WiFi sensing has been rapidly developed for privacy-preserving,
ubiquitous human-sensing applications, enabled by signal processing and deep-learning …

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 …

Action recognition is a major branch of computer vision research. As a widely used
technology, action recognition has been applied to human–computer interaction, intelligent …

Human activity recognition is one of the most studied topics in the field of computer vision. In
recent years, with the availability of RGB-D sensors and powerful deep learning techniques …

Our transportation field has recently witnessed an arms race of neural network-based
trajectory predictors. While these predictors are at the core of many applications such as …

Recently, methods for skeleton-based human activity recognition have been shown to be
vulnerable to adversarial attacks. However, these attack methods require either the full …