I3D-Shufflenet Based Human Action Recognition
In view of difficulty in application of optical flow based human action recognition due to large amount of calculation, a human action recognition algorithm I3D-shufflenet model is proposed combining the advantages of I3D neural network and lightweight model shufflenet. The 5 × 5 convolution kernel...
Main Authors: | Guocheng Liu, Caixia Zhang, Qingyang Xu, Ruoshi Cheng, Yong Song, Xianfeng Yuan, Jie Sun |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-11-01
|
Series: | Algorithms |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-4893/13/11/301 |
Similar Items
-
AR3D: Attention Residual 3D Network for Human Action Recognition
by: Min Dong, et al.
Published: (2021-02-01) -
Skeleton-Based Square Grid for Human Action Recognition With 3D Convolutional Neural Network
by: Wenwen Ding, et al.
Published: (2021-01-01) -
Internal Transfer Learning for Improving Performance in Human Action Recognition for Small Datasets
by: Tian Wang, et al.
Published: (2017-01-01) -
Review of Human Action Recognition Based on Deep Learning
by: QIAN Huifang, YI Jianping, FU Yunhu
Published: (2021-03-01) -
Human Action Monitoring for Healthcare Based on Deep Learning
by: Yongbin Gao, et al.
Published: (2018-01-01)