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Found 9 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.
Heterogeneous Graph-based Trajectory Prediction using Local Map Context and Social Interactions
Precisely predicting the future trajectories of surrounding traffic participants is a crucial but challenging problem in autonomous driving, due to complex interactions between traffic agents, map context and traffic rules.
Context-driven Visual Object Recognition based on Knowledge Graphs
The experimental results provide evidence that the contextual views influence the image representations in the DNN differently and therefore lead to different predictions for the same images.
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.
A Survey on Visual Transfer Learning using Knowledge Graphs
KGs can represent auxiliary knowledge either in an underlying graph-structured schema or in a vector-based knowledge graph embedding.
Learning Visual Models using a Knowledge Graph as a Trainer
However, due to the sole dependence on the image data distribution of the training domain, these models tend to fail when applied to a target domain that differs from their source domain.
Git4Voc: Git-based Versioning for Collaborative Vocabulary Development
Collaborative vocabulary development in the context of data integration is the process of finding consensus between the experts of the different systems and domains.
