arXiv Computer Vision By Chun Liu, Yuxin Wang, Zhenxiang Huo, Linlin Zhu, Tao Xu, Henggang Han

Structure-Aware Matching for Robust UAV Thermal-to-Satellite Geo-Localization

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The paper introduces SAMF, a Structure-Aware Matching Framework designed to improve UAV thermal-to-satellite geo‑localization by exploiting stable cross‑modal structural cues. It comprises a Directional Structure Enhancement Module that captures directional and low‑frequency spatial patterns, and a Modality‑Aware Affine Remapping Module that aligns these enhanced features across modalities. Experiments on Boson‑nighttime and Thermal‑UAV‑Paired datasets demonstrate state‑of‑the‑art performance, with ablation studies confirming the complementary benefits of the two modules.

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arXiv Computer Vision
Aug 27

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.

By Zimin Xia, Mubariz Zaffar, Junsheng Fu, Alexandre Alahi, Julian F. P. Kooij