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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 …
Action recognition based on RGB and skeleton data sets: A survey
Action recognition is a major branch of computer vision research. As a widely used
technology, action recognition has been applied to human–computer interaction, intelligent …
technology, action recognition has been applied to human–computer interaction, intelligent …
Star-transformer: a spatio-temporal cross attention transformer for human action recognition
In action recognition, although the combination of spatio-temporal videos and skeleton
features can improve the recognition performance, a separate model and balancing feature …
features can improve the recognition performance, a separate model and balancing feature …
Revisiting skeleton-based action recognition
Human skeleton, as a compact representation of human action, has received increasing
attention in recent years. Many skeleton-based action recognition methods adopt GCNs to …
attention in recent years. Many skeleton-based action recognition methods adopt GCNs to …
Skeleton aware multi-modal sign language recognition
Sign language is commonly used by deaf or speech impaired people to communicate but
requires significant effort to master. Sign Language Recognition (SLR) aims to bridge the …
requires significant effort to master. Sign Language Recognition (SLR) aims to bridge the …
Unified keypoint-based action recognition framework via structured keypoint pooling
This paper simultaneously addresses three limitations associated with conventional
skeleton-based action recognition; skeleton detection and tracking errors, poor variety of the …
skeleton-based action recognition; skeleton detection and tracking errors, poor variety of the …
Skeleton-RGB integrated highly similar human action prediction in human–robot collaborative assembly
Human–robot collaborative assembly (HRCA) combines the flexibility and adaptability of
humans with the efficiency and reliability of robots during collaborative assembly operations …
humans with the efficiency and reliability of robots during collaborative assembly operations …
Sign language recognition using graph and general deep neural network based on large scale dataset
Sign Language Recognition (SLR) represents a revolutionary technology aiming to
establish communication between hearing impaired and non-hearing impaired …
establish communication between hearing impaired and non-hearing impaired …
Deep learning and RGB-D based human action, human–human and human–object interaction recognition: A survey
Human activity recognition is one of the most studied topics in the field of computer vision. In
recent years, with the availability of RGB-D sensors and powerful deep learning techniques …
recent years, with the availability of RGB-D sensors and powerful deep learning techniques …
Multi-stream general and graph-based deep neural networks for skeleton-based sign language recognition
Sign language recognition (SLR) aims to bridge speech-impaired and general communities
by recognizing signs from given videos. However, due to the complex background, light …
by recognizing signs from given videos. However, due to the complex background, light …