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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 …
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 …
Expansion-squeeze-excitation fusion network for elderly activity recognition
This work focuses on the task of elderly activity recognition, which is a challenging task due
to the existence of individual actions and human-object interactions in elderly activities …
to the existence of individual actions and human-object interactions in elderly activities …
Traffic flow prediction using LSTM with feature enhancement
Long short-term memory (LSTM) is widely used to process and predict events with time
series, but it is difficult to solve exceedingly long-term dependencies, possibly because the …
series, but it is difficult to solve exceedingly long-term dependencies, possibly because the …
Host–parasite: Graph LSTM-in-LSTM for group activity recognition
This article aims to tackle the problem of group activity recognition in the multiple-person
scene. To model the group activity with multiple persons, most long short-term memory …
scene. To model the group activity with multiple persons, most long short-term memory …
Spatiotemporal co-attention recurrent neural networks for human-skeleton motion prediction
Human motion prediction aims to generate future motions based on the observed human
motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling …
motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling …
Coherence constrained graph LSTM for group activity recognition
This work aims to address the group activity recognition problem by exploring human motion
characteristics. Traditional methods hold that the motions of all persons contribute equally to …
characteristics. Traditional methods hold that the motions of all persons contribute equally to …
Hierarchical long short-term concurrent memory for human interaction recognition
In this work, we aim to address the problem of human interaction recognition in videos by
exploring the long-term inter-related dynamics among multiple persons. Recently, Long …
exploring the long-term inter-related dynamics among multiple persons. Recently, Long …
Modeling two-person segmentation and locomotion for stereoscopic action identification: A sustainable video surveillance system
Due to the constantly increasing demand for automatic tracking and recognition systems,
there is a need for more proficient, intelligent and sustainable human activity tracking. The …
there is a need for more proficient, intelligent and sustainable human activity tracking. The …
Participation-contributed temporal dynamic model for group activity recognition
Group activity recognition, a challenging task that a number of individuals occur in the scene
of activity while only a small subset of them participate in, has received increasing attentions …
of activity while only a small subset of them participate in, has received increasing attentions …