Meridian matches metric-semantic primitives across aerial and ground views for training-free global localization in diverse natural environments, reporting 2.4 m average trajectory error over 19 km.
Distribution estimation for global data association via approximate bayesian infer- ence,
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Meridian: Metric-Semantic Primitive Matching for Cross-View Geo-Localization Beyond Urban Environments
Meridian matches metric-semantic primitives across aerial and ground views for training-free global localization in diverse natural environments, reporting 2.4 m average trajectory error over 19 km.