Transformer for skeleton-based action recognition: A review of recent advances

W **n, R Liu, Y Liu, Y Chen, W Yu, Q Miao - Neurocomputing, 2023‏ - Elsevier
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 …

Action recognition based on RGB and skeleton data sets: A survey

R Yue, Z Tian, S Du - Neurocomputing, 2022‏ - Elsevier
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 …

Expansion-squeeze-excitation fusion network for elderly activity recognition

X Shu, J Yang, R Yan, Y Song - IEEE Transactions on Circuits …, 2022‏ - ieeexplore.ieee.org
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 …

Traffic flow prediction using LSTM with feature enhancement

B Yang, S Sun, J Li, X Lin, Y Tian - Neurocomputing, 2019‏ - Elsevier
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 …

Host–parasite: Graph LSTM-in-LSTM for group activity recognition

X Shu, L Zhang, Y Sun, J Tang - IEEE transactions on neural …, 2020‏ - ieeexplore.ieee.org
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 …

Spatiotemporal co-attention recurrent neural networks for human-skeleton motion prediction

X Shu, L Zhang, GJ Qi, W Liu… - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
Human motion prediction aims to generate future motions based on the observed human
motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling …

Coherence constrained graph LSTM for group activity recognition

J Tang, X Shu, R Yan, L Zhang - IEEE transactions on pattern …, 2019‏ - ieeexplore.ieee.org
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 …

Hierarchical long short-term concurrent memory for human interaction recognition

X Shu, J Tang, GJ Qi, W Liu… - IEEE transactions on …, 2019‏ - ieeexplore.ieee.org
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 …

Modeling two-person segmentation and locomotion for stereoscopic action identification: A sustainable video surveillance system

N Khalid, M Gochoo, A Jalal, K Kim - Sustainability, 2021‏ - mdpi.com
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 …

Participation-contributed temporal dynamic model for group activity recognition

R Yan, J Tang, X Shu, Z Li, Q Tian - Proceedings of the 26th ACM …, 2018‏ - dl.acm.org
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 …