Search Results for author:
Found 2 papers, 1 papers with code
SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networks
In this work we propose SCENE, a methodology to encode diverse traffic scenes in heterogeneous graphs and to reason about these graphs using a heterogeneous Graph Neural Network encoder and task-specific decoders.
Ranked #1 on
Node Classification
on BGS
MEAT: Maneuver Extraction from Agent Trajectories
Additionally, an analysis of the datasets and an evaluation of the prediction models based on the agent dynamics is provided.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
