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 …
Skeleton-based action recognition with shift graph convolutional network
Action recognition with skeleton data is attracting more attention in computer vision.
Recently, graph convolutional networks (GCNs), which model the human body skeletons as …
Recently, graph convolutional networks (GCNs), which model the human body skeletons as …
Stronger, faster and more explainable: A graph convolutional baseline 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 State-Of-The-Art (SOTA) …
features over all skeleton joints. However, the complexity of the State-Of-The-Art (SOTA) …
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 …
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 …
Human activity recognition using temporal convolutional neural network architecture
YA Andrade-Ambriz, S Ledesma… - Expert Systems with …, 2022 - Elsevier
In health care and other fields, the detection and recognition of human actions or activities
are essential in the context of human–robot interaction. During the last decade, many …
are essential in the context of human–robot interaction. During the last decade, many …
Learning multi-granular spatio-temporal graph network for skeleton-based action recognition
The task of skeleton-based action recognition remains a core challenge in human-centred
scene understanding due to the multiple granularities and large variation in human motion …
scene understanding due to the multiple granularities and large variation in human motion …
Fuzzy integral-based CNN classifier fusion for 3D skeleton action recognition
Action recognition based on skeleton key joints has gained popularity due to its cost
effectiveness and low complexity. Existing Convolutional Neural Network (CNN) based …
effectiveness and low complexity. Existing Convolutional Neural Network (CNN) based …
Feedback graph convolutional network for skeleton-based action recognition
Skeleton-based action recognition has attracted considerable attention since the skeleton
data is more robust to the dynamic circumstances and complicated backgrounds than other …
data is more robust to the dynamic circumstances and complicated backgrounds than other …