SSRL: Self-Supervised Spatial-Temporal Representation Learning for 3D Action Recognition-Reference-Cited by-同舟云学术

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SSRL: Self-Supervised Spatial-Temporal Representation Learning for 3D Action Recognition

Published:2024-01 Issue:1 Volume:34 Page:274-285
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:

Jin Zhihao¹,Wang Yifan²,Wang Qicong³^ORCID,Shen Yehu²^ORCID,Meng Hongying³^ORCID

Affiliation:

1. Department of Computer Science and Technology, Xiamen University, Xiamen, China

2. College of Mechanical Engineering, Suzhou University of Science and Technology, Suzhou, China

3. Department of Electronic and Electrical Engineering, Brunel University London, Uxbridge, U.K.

Funder

Shenzhen Science and Technology Project

Natural Science Foundation of Fujian Province

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/ielx7/76/10382161/10147284.pdf?arnumber=10147284

Reference62 articles.

1. Microsoft Kinect Sensor and Its Effect

2. Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group

3. Rolling Rotations for Recognizing Human Actions from 3D Skeletal Data

4. Hierarchical recurrent neural network for skeleton based action recognition

5. Spatio-Temporal Attention-Based LSTM Networks for 3D Action Recognition and Detection

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A puzzle questions form training for self-supervised skeleton-based action recognition;Image and Vision Computing;2024-08

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