arXiv Computer Vision
Pixel-wise Geo-registration of Drone and Satellite Images
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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.
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Wrivinder: Towards Spatial Intelligence for Geo-locating Ground Images onto Satellite Imagery
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SkyAnchor: Updating Metric-scale Aerial 3D Gaussian Scenes from Unposed Ground-View Sequences
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Ground-to-Satellite Localization in Unconstrained Image Collections for 3D Scene Reconstruction
arXiv:2608.29211v1 Announce Type: new Abstract: Ground image localization with respect to satellite imagery is a key enabler for metrically-accurate, geo-localized 3D scene reconstruction from uncons...
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GeoLink: A 3D-aware Framework to Improve Generalization for Cross-view Geo-localization
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OpenCVL: An Open, Diverse, and Large-Scale Dataset for Fine-Grained Cross-View Localization
OpenCVL is a large, open dataset for fine-grained cross-view localization, comprising 617,388 ground‑aerial image pairs from 41 European cities. It blends high‑end sensor data with diverse in‑the‑wild images and includes a curation framework to correct pose annotations, enabling reliable evaluation. The dataset also offers cross‑area and snowy test sets to probe generalization, and experiments show that adding noisy in‑the‑wild data improves model performance on clean tests.