mlsanityData to 7 Oct 2026

RSL-Net: Localising in Satellite Images From a Radar on the Ground

arXiv 2001.03233 ↗First posted 9 Jan 2020cs.CV cs.RO eess.IVcited by 18

Not on the map. Why?

Abstract (arXiv)

This paper is about localising a vehicle in an overhead image using FMCW radar mounted on a ground vehicle. FMCW radar offers extraordinary promise and efficacy for vehicle localisation. It is impervious to all weather types and lighting conditions. However the complexity of the interactions between millimetre radar wave and the physical environment makes it a challenging domain. Infrastructure-free large-scale radar-based localisation is in its infancy. Typically here a map is built and suitable techniques, compatible with the nature of sensor, are brought to bear. In this work we eschew the need for a radar-based map; instead we simply use an overhead image -- a resource readily available everywhere. This paper introduces a method that not only naturally deals with the complexity of the signal type but does so in the context of cross modal processing.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jan 2020.

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Citing papers per year: 2021: 4; 2022: 5; 2023: 5; 2024: 2; 2025: 2.

18 papers.

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  1. 2022Visual Cross-View Metric Localization with Dense Uncertainty Estimatescited by 48
  2. 2023Boosting 3-DoF Ground-to-Satellite Camera Localization Accuracy via Geometry-Guided Cross-View Transformercited by 45
  3. 2021Deep Multi-Task Learning for Joint Localization, Perception, and Predictioncited by 22
  4. 2023(LC)2: LiDAR-Camera Loop Constraints For Cross-Modal Place Recognitioncited by 16
  5. 2023View Consistent Purification for Accurate Cross-View Localizationcited by 15
  6. 2024Weakly-supervised Camera Localization by Ground-to-satellite Image Registrationcited by 15
  7. 2021Place recognition survey: An update on deep learning approachescited by 13
  8. 2022Continuous Self-Localization on Aerial Images Using Visual and Lidar Sensorscited by 10
  9. 2021Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learningcited by 8
  10. 2023Energy-Based Models for Cross-Modal Localization using Convolutional Transformerscited by 3
  11. 2022Robust Self-Tuning Data Association for Geo-Referencing Using Lane Markingscited by 2
  12. 2024AGL-NET: Aerial-Ground Cross-Modal Global Localization with Varying Scalescited by 2
6 more
  1. 2022A Survey on Visual Map Localization Using LiDARs and Camerascited by 1
  2. 2025Evaluating Global Geo-alignment for Precision Learned Autonomous Vehicle Localization using Aerial Datacited by 1
  3. 2025RaSCL: Radar to Satellite Crossview Localizationcited by 1
  4. 2021Collaborative Recognition of Feasible Region with Aerial and Ground Robots through DPCNcited by 0
  5. 2022DPCN++: Differentiable Phase Correlation Network for Versatile Pose Registrationcited by 0
  6. 2023Geo-Localization Based on Dynamically Weighted Factor-Graphcited by 0