Dual-encoder networks using vision foundation models and synthetic data achieve accurate cross-view localization for rovers in aerial maps, validated on new real planetary analogue trajectories and synthetic image pairs with particle filter state estimation.
CVM-Net: Cross-View Matching Network for Image- Based Ground-to-Aerial Geo-Localization
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Vision Foundation Models for Domain Generalisable Cross-View Localisation in Planetary Ground-Aerial Robotic Teams
Dual-encoder networks using vision foundation models and synthetic data achieve accurate cross-view localization for rovers in aerial maps, validated on new real planetary analogue trajectories and synthetic image pairs with particle filter state estimation.