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cs.CV2023★ 61 cited
SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networks
Thomas Monninger, Julian Schmidt, Jan Rupprecht +5
Understanding traffic scenes requires considering heterogeneous information about dynamic agents and the static infrastructure. In this work we propose SCENE, a methodology to enco…
cs.CV2022
MEAT: Maneuver Extraction from Agent Trajectories
Julian Schmidt, Julian Jordan, David Raba +2
Advances in learning-based trajectory prediction are enabled by large-scale datasets. However, in-depth analysis of such datasets is limited. Moreover, the evaluation of prediction…