SatMap: Revisiting Satellite Maps as Prior for Online HD Map Construction

We propose SatMap, a camera-satellite fusion-based online vectorized HD map prediction framework. Due to occlusion in perspective view, camera-only models fail to predict accurate map polylines. With a satellite map as prior, SatMap can augment the occluded region with prior information and predict a much accurate HD map. The occluded areas are highlighted in red and magenta.

Abstract

Online high-definition (HD) map construction is an essential part of safe and robust end-to-end autonomous driving (AD) pipeline. Onboard camera-based approaches suffer from limited depth perception and degraded accuracy due to occlusion. In this work, we propose SatMap, an online vectorized HD map estimation method, which integrates satellite map with multi-view camera observations and directly predicts vectorized HD map for downstream prediction and planning modules. Our method leverages lane-level semantics and texture from satellite imagery captured from Bird’s Eye View (BEV) perspective as a global prior, effectively mitigating depth ambiguity and occlusion. In our experiments on nuScenes dataset, SatMap achieves 34.8% mAP performance improvement over Camera-only baseline and 8.5% mAP improvement over Camera-LiDAR fusion baseline. Moreover, we evaluate our model in long range and adverse weather conditions to demonstrate the advantages of using satellite prior map. Source code will be available here.

Paper
Code (Coming Soon)

Architecture

The architecture of our proposed SatMap architecture. First, multi-view image features are extracted and projected to BEV space, which are fused with BEV features extracted from the satellite map. The fused BEV feature is used for decoding vectorized map elements.

Result

Citation

@conference{
  title = {SatMap: Revisiting Satellite Maps as Prior for Online HD Map Construction},
  author = {Mazumder, Kanak and Flohr, Fabian B.},
  booktitle ={ArXiv},
  month = {January},
  year = {2026},
}

Acknowledgement

This work is a result of the joint research project STADT:up (19A22006N). The project is supported by the German Federal Ministry for Economic Affairs and Climate Action (BMWK), based on a decision of the German Bundestag. The author is solely responsible for the content of this publication.