Adaptive Spatial-Temporal Graph-Mixer for Human Motion Prediction-Reference-Cited by-同舟云学术

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Adaptive Spatial-Temporal Graph-Mixer for Human Motion Prediction

Published:2024 Issue: Volume:31 Page:1244-1248
ISSN:1070-9908
Container-title:IEEE Signal Processing Letters
language:
Short-container-title:IEEE Signal Process. Lett.

Author:

Yang Shubo¹^ORCID,Li Haolun²^ORCID,Pun Chi-Man²^ORCID,Du Chun³^ORCID,Gao Hao¹^ORCID

Affiliation:

1. College of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing, China

2. Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau, China

3. School of Science, Tibet University, Tibet, China

Funder

National Natural Science Foundation of China

Science and Technology Development and Fund of Macau SAR

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/97/10380231/10508393.pdf?arnumber=10508393

Reference32 articles.

1. Spatial-Temporal Asynchronous Normalization for Unsupervised 3D Action Representation Learning

2. Deep Representation Learning for Human Motion Prediction and Classification

3. Scale-Adaptive Human Target Tracking for Through-Wall Imaging Radar

4. Motion-Driven Visual Tempo Learning for Video-Based Action Recognition

5. Style machines

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