Unsupervised Video-Based Action Recognition With Imagining Motion and Perceiving Appearance-Reference-Cited by-同舟云学术

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Unsupervised Video-Based Action Recognition With Imagining Motion and Perceiving Appearance

Published:2023-05 Issue:5 Volume:33 Page:2245-2258
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Lin Wei¹^ORCID,Liu Xiaoyu¹^ORCID,Zhuang Yihong¹^ORCID,Ding Xinghao²^ORCID,Tu Xiaotong¹^ORCID,Huang Yue²^ORCID,Zeng Huanqiang³^ORCID

Affiliation:

1. School of Informatics, Xiamen University, Xiamen, China

2. School of Informatics, Institute of Artificial Intelligence, Xiamen University, Xiamen, China

3. School of Engineering and School of Information Science and Engineering, Huaqiao University, Quanzhou, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Link

http://xplorestaging.ieee.org/ielx7/76/10116045/09944692.pdf?arnumber=9944692

Reference75 articles.

1. Unsupervised Deep Learning of Mid-Level Video Representation for Action Recognition

2. STA-CNN: Convolutional Spatial-Temporal Attention Learning for Action Recognition

3. Video Representation Learning by Recognizing Temporal Transformations

4. What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation

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1. Multimodal vision-based human action recognition using deep learning: a review;Artificial Intelligence Review;2024-06-19

2. Coarse-to-Fine Grained Alignment Video Super-Resolution for Underwater Camera;IEEE Transactions on Consumer Electronics;2024-02

3. Unsupervised video-based action recognition using two-stream generative adversarial network;Neural Computing and Applications;2023-12-26

4. Action Behavior Learning Based on a New Multi-Scale Interactive Perception Network;IEEE Access;2023

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