Dual-branch spatio-temporal graph neural networks for pedestrian trajectory prediction-Reference-Cited by-同舟云学术

Dual-branch spatio-temporal graph neural networks for pedestrian trajectory prediction

Published:2023-10 Issue: Volume:142 Page:109633
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Zhang Xingchen^ORCID,Angeloudis Panagiotis,Demiris Yiannis

Funder

Royal Academy of Engineering

Innovate UK

H2020 Marie Skłodowska-Curie Actions

Horizon 2020

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference49 articles.

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2. Holistic LSTM for pedestrian trajectory prediction;Quan;IEEE Trans. Image Process.,2021

3. Pedestrian motion trajectory prediction in intelligent driving from far shot first-person perspective video;Cai;IEEE Trans. Intell. Transp. Syst.,2021

4. DenseCAvoid: real-time navigation in dense crowds using anticipatory behaviors;Sathyamoorthy,2020

5. Robot navigation based on human trajectory prediction and multiple travel modes;Chen;Appl. Sci.,2018

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