Transformer for skeleton-based action recognition: A review of recent advances
Skeleton-based action recognition has rapidly become one of the most popular and
essential research topics in computer vision. The task is to analyze the characteristics of …
essential research topics in computer vision. The task is to analyze the characteristics of …
Unsupervised 3D skeleton-based action recognition using cross-attention with conditioned generation capabilities
Human action recognition plays a pivotal role in various real-world applications, including
surveillance systems, robotics, and occupant monitoring in the car interior. With such a …
surveillance systems, robotics, and occupant monitoring in the car interior. With such a …
GLTA-GCN: Global-local temporal attention graph convolutional network for unsupervised skeleton-based action recognition
H Qiu, Y Wu, MM Duan, C Jin - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Unsupervised skeleton-based action recognition has attracted increasing attention. Existing
methods have several limitations:(1) Many actions are highly related to local joints, which is …
methods have several limitations:(1) Many actions are highly related to local joints, which is …
A convolutional autoencoder model with weighted multi-scale attention modules for 3D skeleton-based action recognition
The 3D skeleton sequences of action can be recognized based on series of meaningful
movements including changes in the direction and geometry features of the body pose. In …
movements including changes in the direction and geometry features of the body pose. In …
Multi-granular spatial-temporal synchronous graph convolutional network for robust action recognition
Abstract Graph Convolutional Networks (GCNs) have shown great potential in skeleton-
based human action recognition. However, due to the diversity and complexity, modeling …
based human action recognition. However, due to the diversity and complexity, modeling …
Attack is good augmentation: Towards skeleton-contrastive representation learning
Contrastive learning, relying on effective positive and negative sample pairs, is beneficial to
learn informative skeleton representations in unsupervised skeleton-based action …
learn informative skeleton representations in unsupervised skeleton-based action …
Hyperpointnet for point cloud sequence-based 3D human action recognition
X Li, Q Huang, T Yang, Q Wu - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Point cloud sequence-based 3D action recognition achieves impressive performance and
efficiency. Conventional approaches for modeling point cloud sequences usually perform …
efficiency. Conventional approaches for modeling point cloud sequences usually perform …
Human activity discovery with automatic multi-objective particle swarm optimization clustering with gaussian mutation and game theory
Despite many advances in Human Activity Recognition (HAR), most existing works are
conducted with supervision. Supervised methods rely on labeled training data. However …
conducted with supervision. Supervised methods rely on labeled training data. However …
Unsupervised view-invariant human posture representation
Most recent view-invariant action recognition and performance assessment approaches rely
on a large amount of annotated 3D skeleton data to extract view-invariant features …
on a large amount of annotated 3D skeleton data to extract view-invariant features …
Scale-Aware Graph Convolutional Network with Part-Level Refinement for Skeleton-Based Human Action Recognition
Graph Convolutional Networks (GCNs) have been widely used in skeleton-based human
action recognition and have achieved promising results. However, current GCN-based …
action recognition and have achieved promising results. However, current GCN-based …