Tavis Shore

2 accepted papers

2025

PEnG: Pose-Enhanced Geo-Localisation

Tavis Shore, Oscar Mendez, Simon Hadfield

RA-L 2025

Cross-view Geo-localisation is typically performed at a coarse granularity, because densely sampled satellite image patches overlap heavily. This heavy overlap would make disambiguating patches very challenging. However, by opting for sparsely sampled patches, prior work has placed an artificial upp

Cited by 3 Source ↗code ↗Scholar ↗

2024

BEV-CV: Birds-Eye-View Transform for Cross-View Geo-Localisation

Tavis Shore, Simon Hadfield, Oscar Mendez

IROS 2024poster

Cross-view image matching for geo-localisation is a challenging problem due to the significant visual difference between aerial and ground-level viewpoints. The method provides localisation capabilities from geo-referenced images, eliminating the need for external devices or costly equipment. This e…

Cited by 1 Source ↗code ↗Scholar ↗