ImagineMap: Enhanced HD Map Construction with SD Maps
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Abstract (arXiv)
Track Mapless demands models to process multi-view images and Standard-Definition (SD) maps, outputting lane and traffic element perceptions along with their topological relationships. We propose a novel architecture that integrates SD map priors to improve lane line and area detection performance. Inspired by TopoMLP, our model employs a two-stage structure: perception and reasoning. The downstream topology head uses the output from the upstream detection head, meaning accuracy improvements in detection significantly boost downstream performance.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 13 of its 13 references that are in the map. First posted on arXiv 22 Dec 2024.
Builds on
13 of 13 references.
References · 13
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- 2023Augmenting Lane Perception and Topology Understanding with Standard Definition Navigation Mapscited by 58
- 2023LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Drivingcited by 57
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1 paper.