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 survey on 3d skeleton-based action recognition using learning method
Three-dimensional skeleton-based action recognition (3D SAR) has gained important
attention within the computer vision community, owing to the inherent advantages offered by …
attention within the computer vision community, owing to the inherent advantages offered by …
Constructing stronger and faster baselines for skeleton-based action recognition
One essential problem in skeleton-based action recognition is how to extract discriminative
features over all skeleton joints. However, the complexity of the recent State-Of-The-Art …
features over all skeleton joints. However, the complexity of the recent State-Of-The-Art …
Decoupling gcn with dropgraph module for skeleton-based action recognition
In skeleton-based action recognition, graph convolutional networks (GCNs) have achieved
remarkable success. Nevertheless, how to efficiently model the spatial-temporal skeleton …
remarkable success. Nevertheless, how to efficiently model the spatial-temporal skeleton …
Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding
Research on depth-based human activity analysis achieved outstanding performance and
demonstrated the effectiveness of 3D representation for action recognition. The existing …
demonstrated the effectiveness of 3D representation for action recognition. The existing …
Dynamic gcn: Context-enriched topology learning for skeleton-based action recognition
raph Convolutional Networks (GCNs) have attracted increasing interests for the task of
skeleton-based action recognition. The key lies in the design of the graph structure, which …
skeleton-based action recognition. The key lies in the design of the graph structure, which …
Point 4d transformer networks for spatio-temporal modeling in point cloud videos
Point cloud videos exhibit irregularities and lack of order along the spatial dimension where
points emerge inconsistently across different frames. To capture the dynamics in point cloud …
points emerge inconsistently across different frames. To capture the dynamics in point cloud …
Richly activated graph convolutional network for robust skeleton-based action recognition
Current methods for skeleton-based human action recognition usually work with complete
skeletons. However, in real scenarios, it is inevitable to capture incomplete or noisy …
skeletons. However, in real scenarios, it is inevitable to capture incomplete or noisy …
Learning progressive joint propagation for human motion prediction
Despite the great progress in human motion prediction, it remains a challenging task due to
the complicated structural dynamics of human behaviors. In this paper, we address this …
the complicated structural dynamics of human behaviors. In this paper, we address this …
Skelemotion: A new representation of skeleton joint sequences based on motion information for 3d action recognition
Due to the availability of large-scale skeleton datasets, 3D human action recognition has
recently called the attention of computer vision community. Many works have focused on …
recently called the attention of computer vision community. Many works have focused on …