HGeo-TopoMap: Boosting Topological Mapping with Hierarchical Geometric Priors
Topological maps are key outputs of autonomous driving perception systems, delivering essential road information for path planning. They identify instances such as centerlines and traffic signs, along with their connectivity relationships. Due to the lack of explicit markings for centerlines in real-world environments, the detection of centerline instances remains a significant challenge. To tackle this problem, we propose HGeo-TopoMap, which leverages an explicit prior map and implicit spatial relations to hierarchically boost topological mapping. First, a geometric adaptive learning module i
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- LinkedLinked via arxiv author · 85%Siyu Li →
“HGeo-TopoMap: Boosting Topological Mapping with Hierarchical Geometric Priors”
- LinkedLinked via arxiv author · 85%Kunyu Peng →
“HGeo-TopoMap: Boosting Topological Mapping with Hierarchical Geometric Priors”
- LinkedLinked via arxiv author · 85%Di Wen →
“HGeo-TopoMap: Boosting Topological Mapping with Hierarchical Geometric Priors”
- LinkedLinked via arxiv author · 85%Beiping Hou →
“HGeo-TopoMap: Boosting Topological Mapping with Hierarchical Geometric Priors”
- LinkedLinked via arxiv author · 85%Zhiyong Li →
“HGeo-TopoMap: Boosting Topological Mapping with Hierarchical Geometric Priors”
- LinkedLinked via arxiv author · 85%Kailun Yang →
“HGeo-TopoMap: Boosting Topological Mapping with Hierarchical Geometric Priors”