arXiv Computer Vision
Ground-to-Satellite Localization in Unconstrained Image Collections for 3D Scene Reconstruction
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Beyond 2D Matching: A Unified Single-Stage Framework for Geometry-Aware Cross-View Object Geo-Localization
arXiv:2606. 30576v1 Announce Type: cross Abstract: Cross-view object geo-localization (CVOGL) aims to locate a target object from a query view (e.
arXiv Computer Vision
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Pixel-wise Geo-registration of Drone and Satellite Images
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arXiv Computer Vision
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Wrivinder: Towards Spatial Intelligence for Geo-locating Ground Images onto Satellite Imagery
arXiv:2602.14929v2 Announce Type: replace Abstract: Aligning ground-level imagery with geo-registered satellite maps is crucial for mapping, navigation, and situational awareness, yet remains challen...
arXiv Computer Vision
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SkyAnchor: Updating Metric-scale Aerial 3D Gaussian Scenes from Unposed Ground-View Sequences
arXiv:2609.13903v1 Announce Type: new Abstract: We study how to update a pre-built aerial scene with a newly captured, unposed ground-view sequence. The aerial scene already contains a reliable metri...
arXiv Computer Vision
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GeoLink: A 3D-aware Framework to Improve Generalization for Cross-view Geo-localization
arXiv:2604.13183v4 Announce Type: replace Abstract: Generalizable cross-view geo-localization aims to match the same location across views in unseen regions and conditions without GPS supervision. It...
Hugging Face Trending Papers
Aug 10
Warp-free Cross-view Geo-localization via Feature-space Consensus Mining
Cross-view geo-localization is challenging due to drastic viewpoint changes and large appearance discrepancies between street-level and satellite imagery. Although existing methods often use geometric warping to expose co-visible cues, such transformations rely on restrictive spatial assumptions and inevitably introduce severe visual distortions under view-dependent visibility, yielding noisy supervision and fragile correspondences.