Apr 15, 2024 · CSGAT-Net models the physical environment and pedestrian behavior information in the scene as a semantic map, and it leverages graph attention ...

CSGAT-Net models the physical environment and pedestrian behavior information in the scene as a semantic map, and it leverages graph attention networks to ...

CSGAT-Net models the physical environment and pedestrian behavior information in the scene as a semantic map, and it leverages graph attention networks to ...

CSGAT-Net: a conditional pedestrian trajectory prediction network based on scene semantic maps and spatiotemporal graph attention.

CSGAT-Net: a conditional pedestrian trajectory prediction network based on scene semantic maps and spatiotemporal graph attention. Authors. Yang, Xin; Fan ...

Dec 5, 2023 · SGAMTE-Net first extracts the spatiotemporal features of pedestrians by combining a Feature Extractor with a heterogeneous spatiotemporal graph ...

Aug 23, 2024 · CSGAT-Net: a conditional pedestrian trajectory prediction network based on scene semantic maps and spatiotemporal graph attention. Neural ...

CSGAT-Net: a conditional pedestrian trajectory prediction network based on scene semantic maps and spatiotemporal graph attention. Article. Full-text ...

CSGAT-Net: a conditional pedestrian trajectory prediction network based on scene semantic maps and spatiotemporal graph attention. Neural Computing and ...

This is a list of the latest research materials (datasets, papers, and codes) related to traffic agent trajectory prediction.