HD Map Construction
HD: High-Definition · Also known as MAP
Overview
The field builds detailed road maps—such as lane boundaries, dividers, and connectivity—from vehicle cameras, LiDAR, radar, aerial imagery, and geographic data, supporting navigation, planning, and simulation. Common approaches use bird’s-eye-view transformers to predict vectorized map elements, with sensor fusion, geometric priors, and temporal consistency to improve structure across views and drives. Research also explores crowdsourced map aggregation, semi-supervised learning, and generative models, with nuScenes, Argoverse 2, and OpenLane-V2 among the evaluation settings. A central challenge is maintaining accurate geometry and topology despite localization errors, missing or changing sensor views, and geographic variation, while scaling reliable maps beyond individual vehicle observations.
Latest papers
39 papers5 papers in the last four weeks, up 67% on the four weeks before. 0.0% of all new papers.