Ground-to-Satellite Localization in Unconstrained Image Collections for 3D Scene Reconstruction
Ground image localization with respect to satellite imagery is a key enabler for metrically-accurate, geo-localized 3D scene reconstruction from unconstrained image collections. Existing cross-view localization methods have strict requirements such as panoramic imagery or known initial locations, limiting their applicability for in-the-wild reconstruction settings. We propose a robust hierarchical cross-view localization framework that leverages geometric constraints from Structure-from-Motion (SfM) models derived from unconstrained ground image collections. Our method generates coarse-to-fine pose hypotheses through a cross-view matching approach and aggregates noisy predictions across S...
| Authors | Angel Daruna, Ben Southall, Niluthpol Chowdhury Mithun et al. |
|---|---|
| Primary category | cs.CV |
| Published | 29 August 2026 |
| Last updated at source | 29 August 2026 |
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