Pedestrian Trajectory Prediction via Window Attention and Spatial Graph Interaction Network

Pedestrian Trajectory Prediction via Window Attention and Spatial Graph Interaction Network

The accuracy of pedestrian trajectory prediction is crucial for the safety of autonomous driving systems. However, the task still faces challenges in modeling long-term dependencies, complex spatial interactions, and multi-scale feature fusion. To address these issues, this paper proposes the WAGIN...

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Bibliographic Details
Main Authors: Xiang Gu, Chao Li, Jie Yang, Jing Wang, Qiwei Huang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Pedestrian trajectory prediction
autonomous driving
window attention
spatiotemporal feature learning
spatial interaction
multi-scale dilated convolution
Online Access:https://ieeexplore.ieee.org/document/11015790/
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https://ieeexplore.ieee.org/document/11015790/

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