Human action recognition from various data modalities: A review
Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …
each action. It has a wide range of applications, and therefore has been attracting increasing …
A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions
Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …
the computer vision. It has critical application in wide variety of tasks including gaming …
Human action recognition using attention based LSTM network with dilated CNN features
Human action recognition in videos is an active area of research in computer vision and
pattern recognition. Nowadays, artificial intelligence (AI) based systems are needed for …
pattern recognition. Nowadays, artificial intelligence (AI) based systems are needed for …
Attention, please! A survey of neural attention models in deep learning
In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …
limited ability to process competing sources, attention mechanisms select, modulate, and …
A comprehensive study of deep video action recognition
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 …
last decade, we have witnessed great advancements in video action recognition thanks to …
A review of convolutional-neural-network-based action recognition
G Yao, T Lei, J Zhong - Pattern Recognition Letters, 2019 - Elsevier
Video action recognition is widely applied in video indexing, intelligent surveillance,
multimedia understanding, and other fields. Recently, it was greatly improved by …
multimedia understanding, and other fields. Recently, it was greatly improved by …
[HTML][HTML] Efficient activity recognition using lightweight CNN and DS-GRU network for surveillance applications
Recognizing human activities has become a trend in smart surveillance that contains
several challenges, such as performing effective analyses of huge video data streams, while …
several challenges, such as performing effective analyses of huge video data streams, while …
Asymmetric 3d convolutional neural networks for action recognition
Abstract Convolutional Neural Network based action recognition methods have achieved
significant improvements in recent years. The 3D convolution extends the 2D convolution to …
significant improvements in recent years. The 3D convolution extends the 2D convolution to …
Recurrent spatial-temporal attention network for action recognition in videos
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 …
action recognition in videos. However, videos are of high dimensionality and contain rich …
Recognizing sports activities from video frames using deformable convolution and adaptive multiscale features
L **ao, Y Cao, Y Gai, E Khezri, J Liu… - Journal of Cloud …, 2023 - Springer
Automated techniques for evaluating sports activities inside dynamic frames are highly
dependent on advanced sports analysis by smart machines. The monitoring of individuals …
dependent on advanced sports analysis by smart machines. The monitoring of individuals …