Recent advances in video-based human action recognition using deep learning: A review
Video-based human action recognition has become one of the most popular research areas
in the field of computer vision and pattern recognition in recent years. It has a wide variety of …
in the field of computer vision and pattern recognition in recent years. It has a wide variety of …
A union of deep learning and swarm-based optimization for 3D human action recognition
Abstract Human Action Recognition (HAR) is a popular area of research in computer vision
due to its wide range of applications such as surveillance, health care, and gaming, etc …
due to its wide range of applications such as surveillance, health care, and gaming, etc …
Deep visual attention prediction
In this paper, we aim to predict human eye fixation with view-free scenes based on an end-to-
end deep learning architecture. Although convolutional neural networks (CNNs) have made …
end deep learning architecture. Although convolutional neural networks (CNNs) have made …
Nddr-cnn: Layerwise feature fusing in multi-task cnns by neural discriminative dimensionality reduction
In this paper, we propose a novel Convolutional Neural Network (CNN) structure for general-
purpose multi-task learning (MTL), which enables automatic feature fusing at every layer …
purpose multi-task learning (MTL), which enables automatic feature fusing at every layer …
Action recognition based on joint trajectory maps using convolutional neural networks
Recently, Convolutional Neural Networks (ConvNets) have shown promising performances
in many computer vision tasks, especially image-based recognition. How to effectively use …
in many computer vision tasks, especially image-based recognition. How to effectively use …
Adaptive fusion and category-level dictionary learning model for multiview human action recognition
Human actions are often captured by multiple cameras (or sensors) to overcome the
significant variations in viewpoints, background clutter, object speed, and motion patterns in …
significant variations in viewpoints, background clutter, object speed, and motion patterns in …
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 …
Action recognition based on joint trajectory maps with convolutional neural networks
Abstract Convolutional Neural Networks (ConvNets) have recently shown promising
performance in many computer vision tasks, especially image-based recognition. How to …
performance in many computer vision tasks, especially image-based recognition. How to …
Co-attentive multi-task convolutional neural network for facial expression recognition
Abstract Previous research on Facial Expression Recognition (FER) assisted by facial
landmarks mainly focused on single-task learning or hard-parameter sharing based multi …
landmarks mainly focused on single-task learning or hard-parameter sharing based multi …
Advances in human action recognition: an updated survey
SAR Abu‐Bakar - IET Image Processing, 2019 - Wiley Online Library
Research in human activity recognition (HAR) has seen tremendous growth and
continuously receiving attention from both the Computer Vision and the Image Processing …
continuously receiving attention from both the Computer Vision and the Image Processing …