ARP-STGCN: a fast attraction–repulsion-potential based spatio-temporal graph convolutional network with imputation for pedestrian trajectory prediction

Abstract Pedestrian trajectory prediction is a critical task in autonomous systems and smart city applications, where predicting the future movement of pedestrians based on observed data is essential for decision-making. In this work, we propose ARP-STGCN, a novel approach that simultaneously addres...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Bin Fang, Fangtao Qin, Yi Wang
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	Springer 2025-10-01
Sarja:	Complex & Intelligent Systems
Aiheet:	Trajectory prediction Hybrid directional potential Graph convolutional network Missing data imputation
Linkit:	https://doi.org/10.1007/s40747-025-02068-4
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