A comprehensive survey of vision-based human action recognition methods
Although widely used in many applications, accurate and efficient human action recognition
remains a challenging area of research in the field of computer vision. Most recent surveys …
remains a challenging area of research in the field of computer vision. Most recent surveys …
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 …
Self-supervised visual feature learning with deep neural networks: A survey
Large-scale labeled data are generally required to train deep neural networks in order to
obtain better performance in visual feature learning from images or videos for computer …
obtain better performance in visual feature learning from images or videos for computer …
Tcgl: Temporal contrastive graph for self-supervised video representation learning
Video self-supervised learning is a challenging task, which requires significant expressive
power from the model to leverage rich spatial-temporal knowledge and generate effective …
power from the model to leverage rich spatial-temporal knowledge and generate effective …
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 deep learning approach for intrusion detection using recurrent neural networks
C Yin, Y Zhu, J Fei, X He - Ieee Access, 2017 - ieeexplore.ieee.org
Intrusion detection plays an important role in ensuring information security, and the key
technology is to accurately identify various attacks in the network. In this paper, we explore …
technology is to accurately identify various attacks in the network. In this paper, we explore …
Temporal segment networks for action recognition in videos
We present a general and flexible video-level framework for learning action models in
videos. This method, called temporal segment network (TSN), aims to model long-range …
videos. This method, called temporal segment network (TSN), aims to model long-range …
Temporal segment networks: Towards good practices for deep action recognition
Deep convolutional networks have achieved great success for visual recognition in still
images. However, for action recognition in videos, the advantage over traditional methods is …
images. However, for action recognition in videos, the advantage over traditional methods is …
Convolutional two-stream network fusion for video action recognition
C Feichtenhofer, A Pinz… - Proceedings of the IEEE …, 2016 - openaccess.thecvf.com
Abstract Recent applications of Convolutional Neural Networks (ConvNets) for human action
recognition in videos have proposed different solutions for incorporating the appearance …
recognition in videos have proposed different solutions for incorporating the appearance …
Automatic classification of defective photovoltaic module cells in electroluminescence images
Electroluminescence (EL) imaging is a useful modality for the inspection of photovoltaic (PV)
modules. EL images provide high spatial resolution, which makes it possible to detect even …
modules. EL images provide high spatial resolution, which makes it possible to detect even …