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A survey on intelligent human action recognition techniques
Human Action Recognition is an essential research area in computer vision due to its automated nature of video monitoring. Human Action Recognition...
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Multimodal human action recognition based on spatio-temporal action representation recognition model
Human action recognition methods based on single-modal data lack adequate information. It is necessary to propose the methods based on multimodal...
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Unsupervised open-world human action recognition
Open-world recognition (OWR) is an important field of research that strives to develop machine learning models capable of identifying and learning...
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Swin-Fusion: Swin-Transformer with Feature Fusion for Human Action Recognition
Human action recognition based on still images is one of the most challenging computer vision tasks. In the past decade, convolutional neural...
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Multi-stream network with key frame sampling for human action recognition
Human action recognition is a challenging task in the field of computer vision, where deep learning-based methods have made significant progress....
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Utilizing CPG-3D, graph theory anchored approach to recognize human action recognition
Graph theory originated as a fun way to solve math problems, but it has now evolved into a significant mathematics subject with several applications...
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Depth-based human action recognition using histogram of templates
In this paper, we propose an efficient, fast, and easy-to-implement method for recognizing human actions in depth image sequences. In this method,...
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Improving zero-shot action recognition using human instruction with text description
Zero-shot action recognition, which recognizes actions in videos without having received any training examples, is gaining wide attention considering...
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Integrating Human Parsing and Pose Network for Human Action Recognition
Human skeletons and RGB sequences are both widely-adopted input modalities for human action recognition. However, skeletons lack appearance features...
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AP-TransNet: a polarized transformer based aerial human action recognition framework
Drones are widespread and actively employed in a variety of applications due to their low cost and quick mobility and enabling new forms of action...
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Unethical human action recognition using deep learning based hybrid model for video forensics
With the rapid growth in multimedia collections around the world, video forensics faces new obstacles in recognizing human actions under video...
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Semantic-guided multi-scale human skeleton action recognition
With the development of depth sensors and pose estimation algorithms, action recognition technology based on the human skeleton has attracted wide...
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ConvST-LSTM-Net: convolutional spatiotemporal LSTM networks for skeleton-based human action recognition
Human action recognition (HAR) emphases on perceiving and identifying the action behavior done by humans within an image/video. The HAR activities...
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Skeleton-based human action recognition by fusing attention based three-stream convolutional neural network and SVM
This work proposes a method, aiming the 3D skeleton sequence, for the human action recognition by fusing the attention-based three-stream...
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Multimodal vision-based human action recognition using deep learning: a review
Vision-based Human Action Recognition (HAR) is a hot topic in computer vision. Recently, deep-based HAR has shown promising results. HAR using a...
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A key-points-assisted network with transfer learning for precision human action recognition in still images
Still image-based human action recognition is a highly sought-after but challenging field in computer vision, and such challenge mainly stems from...
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A novel algorithm for human action recognition in compressed domain using attention-guided approach
Herein, a novel methodology is proposed for real-time human activity detection and recognition in a compressed domain of videos using motion vectors...
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Structural feature representation and fusion of human spatial cooperative motion for action recognition
Aiming at the cooperative relationship of human body parts in the process of action execution, we propose an action recognition method based on the...
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Human Action Recognition Based on LSTM Neural Network Algorithm
As a special recursive neural network, LSTM can avoid the dependency problem of RNN long-term memory to a certain extent. Although the data flow...
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Insights into aerial intelligence: assessing CNN-based algorithms for human action recognition and object detection in diverse environments
Today’s era follows a data-driven decision process for large-scale environment analysis. Aerial view-based decision process plays a key role in...
