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