Lu-Ying Zhao

CAFR: Context-Aware Feature Refinement for Narrow Field-of-View Cross-View Geo-Localization

This work proposes context-aware feature refinement (CAFR), a novel feature learning approach that converts geometric priors within overlapping regions into differentiable supervision signals that directly constrain the cross-attention matrices of features, thereby steering representation learning.