Video action recognition is widely applied in video indexing, intelligent surveillance,
multimedia understanding, and other fields. Recently, it was greatly improved by …

Video-based human action recognition is currently one of the most active research areas in
computer vision. Various research studies indicate that the performance of action …

Video action recognition is one of the representative tasks for video understanding. Over the
last decade, we have witnessed great advancements in video action recognition thanks to …

Human motion recognition is one of the most important branches of human-centered
research activities. In recent years, motion recognition based on RGB-D data has attracted …

Analyzing videos of human actions involves understanding the temporal relationships
among video frames. State-of-the-art action recognition approaches rely on traditional …

The convolutional neural network architecture has different components like convolution and
pooling. The pooling is crucial component placed after the convolution layer. It plays a vital …

Human Action Recognition (HAR) is the classification of an action performed by a human.
The goal of this study was to recognize human actions in action video sequences. We …

We explore a class of end-to-end learnable models wherein data processing nodes (or
network layers) are defined in terms of desired behavior rather than an explicit forward …

Recent years have witnessed the popularity of using recurrent neural network (RNN) for
action recognition in videos. However, videos are of high dimensionality and contain rich …

Due to its capacity to gather vast, high-level data about human activity from wearable or
stationary sensors, human activity recognition substantially impacts people's day-to-day …