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We describe a light-weight, weather and lighting invariant, Semantic Bird'sEye View (S-BEV) signature for vision-based vehicle re-localization. Atopological map of S-BEV signatures is created during the first traversal ofthe route, which are used for coarse localization in subsequent routetraversal. A fine-grained localizer is then trained to output the global 3-DoFpose of the vehicle using its S-BEV and its coarse localization. We conductexperiments on vKITTI2 virtual dataset and show the potential of the S-BEV tobe robust to weather and lighting. We also demonstrate results with 2 vehicleson a 22 km long highway route in the Ford AV dataset.

S-BEV: Semantic Birds-Eye View Representation for Weather and Lighting Invariant 3-DoF Localization