Search Results for author:
Found 4 papers, 1 papers with code
SocialFormer: Social Interaction Modeling with Edge-enhanced Heterogeneous Graph Transformers for Trajectory Prediction
Accurate trajectory prediction is crucial for ensuring safe and efficient autonomous driving.
SemanticFormer: Holistic and Semantic Traffic Scene Representation for Trajectory Prediction using Knowledge Graphs
Trajectory prediction in autonomous driving relies on accurate representation of all relevant contexts of the driving scene including traffic participants, road topology, traffic signs as well as their semantic relations to each other.
nuScenes Knowledge Graph -- A comprehensive semantic representation of traffic scenes for trajectory prediction
Further, we present nuScenes Knowledge Graph (nSKG), a knowledge graph for the nuScenes dataset, that models explicitly all scene participants and road elements, as well as their semantic and spatial relationships.
A Survey on Knowledge Graph-based Methods for Automated Driving
However, recent progress in knowledge graph embeddings and graph neural networks allows to applying machine learning to graph-structured data.
