The goal of semantic segmentation is to segment the input image according to semantic
information and predict the semantic category of each pixel from a given label set. With the …

Abstract Human Action Recognition (HAR) involves human activity monitoring task in
different areas of medical, education, entertainment, visual surveillance, video retrieval, as …

Although widely used in many applications, accurate and efficient human action recognition
remains a challenging area of research in the field of computer vision. Most recent surveys …

In this work, we address human activity and hand gesture recognition problems using 3D
data sequences obtained from full-body and hand skeletons, respectively. To this aim, we …

Human action recognition systems use data collected from a wide range of sensors to
accurately identify and interpret human actions. One of the most challenging issues for …

Human action recognition has a wide range of applications including biometrics,
surveillance, and human computer interaction. The use of multimodal sensors for human …

Human activity recognition (HAR) is a very active yet challenging and demanding area of
computer science. Due to the articulated nature of human motion, it is not trivial to detect …

A number of review or survey articles have previously appeared on human action
recognition where either vision sensors or inertial sensors are used individually …

In this paper, we present a method (Action-Fusion) for human action recognition from depth
maps and posture data using convolutional neural networks (CNNs). Two input descriptors …

This paper aims to improve privacy-preserving visual recognition, an increasingly
demanded feature in smart camera applications, by formulating a unique adversarial …