With the wide deployment of Internet of Things monitoring terminals, a tremendous number
of videos are accumulated continuously. Big data processing and analysis-based action …

Intelligent terminal based action recognition is important to smart cities. However, due to the
dependency on training data and high complexity of extracting information, the existing …

Compressed video action recognition has received significant attention due to its potential
for reducing storage and computational costs. However, the current methods typically only …

RGB-based Transformer methods for video action recognition have achieved advanced
results recently. However, Transformer lacks local details, leading to the accuracy …

Current compressed video action recognition methods are mainly based on complete data.
However, in a real transmission scenario, the compressed video packets are usually …

Modeling and recognizing video activities from videos are key parts of many promising
applications such as visual surveillance, human–computer interaction, and video …

In this article, we study the problem of video-based action recognition. We improve the
action recognition performance by finding an effective temporal and appearance …

Compressed video action recognition has gained significant attention recently due to its
ability to replace the raw video with I-frames and compressed motion clues, such as motion …

Recognizing actions according to video features is an important problem in a wide scope of
applications. In this paper, we propose a temporal scale-invariant deep learning framework …

Modeling spatiotemporal representations is one of the most essential yet challenging issues
in video action recognition. Existing methods lack the capacity to accurately model either the …