Convolutional neural networks have achieved great success in many computer vision tasks.
However, it is still challenging for action recognition in videos due to the intrinsically …

Action recognition is one of the important computer vision tasks, which has many
applications. This paper proposes a Multi-cue based Four-stream 3D ResNets (MF3D) …

Two-stream network architecture has the ability to capture temporal and spatial features from
videos simultaneously and has achieved excellent performance on video action recognition …

Efficient action recognition aims to classify a video clip into a specific action category with a
low computational cost. It is challenging since the integrated spatial-temporal calculation …

Action recognition is a challenging and important problem in a myriad of significant fields,
such as intelligent robots and video surveillance. In recent years, deep learning and neural …

Human action recognition plays a significant part in the research community due to its
emerging applications. A variety of approaches have been proposed to resolve this problem …

Action recognition in videos, which contains many complex and semantic contents, is still a
challenging task in computer vision research. In this paper, we propose a novel attention …

Action Recognition is a fundamental task in computer vision field, with a wide range of
applications in autonomous driving, security monitoring, etc. However, previous action …

Research in human action recognition has accelerated significantly since the introduction of
powerful machine learning tools such as Convolutional Neural Networks (CNNs). However …

Recognizing actions in videos is not a trivial task because video is an information-intensive
media and includes multiple modalities. Moreover, on each modality, an action may only …