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

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

Video action recognition methods based on deep learning can be divided into two types: two-
dimensional convolutional networks (2D-ConvNets) relied and three-dimensional …

Action recognition in video is widely applied in video indexing, intelligent surveillance,
multimedia understanding, and other fields. A typical human action contains the …

The two-stream CNNs prove very successful for video-based action recognition. However,
the classical two-stream CNNs are time costly, mainly due to the bottleneck of calculating …

As an important issue in video classification, human action recognition is becoming a hot
topic in computer vision. The ways of effectively representing the spatial static and temporal …

In this paper, we introduce a novel framework for video-based action recognition, In this
paper, we introduce a novel framework for video-based action recognition, which …

Human action recognition analyzes the behavior in a scene according to the spatiotemporal
features carried in image sequences. Existing works suffers from ineffective spatial–temporal …

Abstract Two-stream Convolutional Networks (ConvNets) have achieved great success in
video action recognition. Research also shows that early fusion of the two-stream ConvNets …

In the deep learning-based video action recognition, the function of the neural network is to
acquire spatial information, motion information, and the associated information of the above …