Human action recognition via multi-task learning base on spatial–temporal feature

2015 ◽  
Vol 320 ◽  
pp. 418-428 ◽  
Author(s):  
Wenzhong Guo ◽  
Guolong Chen
Keyword(s):  
Action Recognition ◽  
Human Action Recognition ◽  
Human Action ◽  
Task Learning ◽  
Temporal Feature

Human Action Recognition Using Spatio-Temporal Multiplier Network and Attentive Correlated Temporal Feature

2021 ◽  
Author(s):  
C. Indhumathi ◽  
V. Murugan ◽  
G. Muthulakshmii
Keyword(s):  
Action Recognition ◽  
State Of The Art ◽  
Human Action Recognition ◽  
Human Action ◽  
Regional Correlation ◽  
Temporal Features ◽  
Adaptive Motion ◽  
Spatio Temporal ◽  
Inter Frame ◽  
Temporal Feature

Nowadays, action recognition has gained more attention from the computer vision community. Normally for recognizing human actions, spatial and temporal features are extracted. Two-stream convolutional neural network is used commonly for human action recognition in videos. In this paper, Adaptive motion Attentive Correlated Temporal Feature (ACTF) is used for temporal feature extractor. The temporal average pooling in inter-frame is used for extracting the inter-frame regional correlation feature and mean feature. This proposed method has better accuracy of 96.9% for UCF101 and 74.6% for HMDB51 datasets, respectively, which are higher than the other state-of-the-art methods.

Multi-Domain and Multi-Task Learning for Human Action Recognition

2019 ◽  
Vol 28 (2) ◽  
pp. 853-867 ◽  
Author(s):  
An-An Liu ◽  
Ning Xu ◽  
Wei-Zhi Nie ◽  
Yu-Ting Su ◽  
Yong-Dong Zhang
Keyword(s):  
Action Recognition ◽  
Human Action Recognition ◽  
Human Action ◽  
Task Learning

Single/multi-view human action recognition via regularized multi-task learning

2015 ◽  
Vol 151 ◽  
pp. 544-553 ◽  
Author(s):  
An-An Liu ◽  
Ning Xu ◽  
Yu-Ting Su ◽  
Hong Lin ◽  
Tong Hao ◽  
...  
Keyword(s):  
Action Recognition ◽  
Human Action Recognition ◽  
Human Action ◽  
Task Learning
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