Learning progressive joint propagation for human motion prediction

Learning progressive joint propagation for human motion prediction

Despite the great progress in human motion prediction, it remains a challenging task due to the complicated structural dynamics of human behaviors. In this paper, we address this problem in three aspects. First, to capture the long-range spatial correlations and temporal dependencies, we apply a tra...

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Bibliographic Details
Main Authors: Cai, Yujun, Huang, Lin, Wang, Yiwei, Cham, Tat-Jen, Cai, Jianfei, Yuan, Junsong, Liu, Jun, Yang, Xu, Zhu, Yiheng, Shen, Xiaohui, Liu, Ding, Liu, Jing, Thalmann, Nadia Magnenat
Other Authors: School of Computer Science and Engineering
Format: Conference Paper
Language:English
Published: 2020
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
3D Motion Prediction
Transformer Network
Online Access:https://hdl.handle.net/10356/144139

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