Leveraging Semantic Maps for City-Scale Cross-View Localization

arXiv:2607.25215v1 Announce Type: new Abstract: We want robots to localize in previously untraversed environments against commonly available prior data. Rich semantic data available from OpenStreetMap can be useful in this task. However, existing methods either ignore this semantic information, directly matching panoramas and overhead imagery, or dramatically compress the semantic information, working with a small set of fixed classes. To leverage this rich semantic information, two challenges n...