3D point cloud data processing with machine learning for construction and infrastructure applications: A comprehensive review
Point clouds are increasingly being used to improve productivity, quality, and safety
throughout the life cycle of construction and infrastructure projects. While applicable for …
throughout the life cycle of construction and infrastructure projects. While applicable for …
A review of machine learning-based human activity recognition for diverse applications
Human activity recognition (HAR) is a very active yet challenging and demanding area of
computer science. Due to the articulated nature of human motion, it is not trivial to detect …
computer science. Due to the articulated nature of human motion, it is not trivial to detect …
Human activity recognition via hybrid deep learning based model
In recent years, Human Activity Recognition (HAR) has become one of the most important
research topics in the domains of health and human-machine interaction. Many Artificial …
research topics in the domains of health and human-machine interaction. Many Artificial …
Multi-scale spatial temporal graph convolutional network for skeleton-based action recognition
Graph convolutional networks have been widely used for skeleton-based action recognition
due to their excellent modeling ability of non-Euclidean data. As the graph convolution is a …
due to their excellent modeling ability of non-Euclidean data. As the graph convolution is a …
3d human action representation learning via cross-view consistency pursuit
In this work, we propose a Cross-view Contrastive Learning framework for unsupervised 3D
skeleton-based action representation (CrosSCLR), by leveraging multi-view complementary …
skeleton-based action representation (CrosSCLR), by leveraging multi-view complementary …
Global context-aware attention lstm networks for 3d action recognition
Abstract Long Short-Term Memory (LSTM) networks have shown superior performance in
3D human action recognition due to their power in modeling the dynamics and …
3D human action recognition due to their power in modeling the dynamics and …
Convolutional neural networks and long short-term memory for skeleton-based human activity and hand gesture recognition
In this work, we address human activity and hand gesture recognition problems using 3D
data sequences obtained from full-body and hand skeletons, respectively. To this aim, we …
data sequences obtained from full-body and hand skeletons, respectively. To this aim, we …
First-person hand action benchmark with rgb-d videos and 3d hand pose annotations
G Garcia-Hernando, S Yuan… - Proceedings of the …, 2018 - openaccess.thecvf.com
In this work we study the use of 3D hand poses to recognize first-person dynamic hand
actions interacting with 3D objects. Towards this goal, we collected RGB-D video sequences …
actions interacting with 3D objects. Towards this goal, we collected RGB-D video sequences …
Skeleton-based human action recognition with global context-aware attention LSTM networks
Human action recognition in 3D skeleton sequences has attracted a lot of research attention.
Recently, long short-term memory (LSTM) networks have shown promising performance in …
Recently, long short-term memory (LSTM) networks have shown promising performance in …
Hierarchical recurrent neural network for skeleton based action recognition
Human actions can be represented by the trajectories of skeleton joints. Traditional methods
generally model the spatial structure and temporal dynamics of human skeleton with hand …
generally model the spatial structure and temporal dynamics of human skeleton with hand …