arXiv Computer Vision By Jiarui Zeng, Kun Shi, Chiman Vong, Zhedong Zheng

SatFix: Absolute Visual Localization of UAVs in Satellite Maps from a Single Oblique Image

Read the original on arXiv Computer Vision →

SatFix is a feed‑forward framework that performs absolute visual localization of UAVs in satellite maps using a single oblique image or a short multi‑view clip. It replaces traditional cross‑view retrieval by regressing a continuous 3‑DoF pose—2D position and heading—directly from satellite‑grid features without requiring a 3D map or auxiliary sensors. On the newly introduced University‑Metric dataset, SatFix localizes over half of test frames within 50 m and achieves median errors of 45.66 m and 20.81° with a single view, improving further with multiple views.

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arXiv Computer Vision
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SatNav: A Scalable Benchmark for Long-Horizon UAV Vision-Language Navigation from Satellite Imagery

SatNav is a new, scalable benchmark for long‑horizon vision‑language navigation (VLN) with unmanned aerial vehicles (UAVs), built from high‑resolution satellite imagery. It generates 118,000 navigation episodes across 59 scenes in 18 cities, using satellite crops to approximate UAV nadir views and featuring three task families—Boundary, Landmark, and Route—to test long‑term memory and geospatial reasoning. The benchmark also introduces SwiftVLN, a modular framework for memory component experimentation, and demonstrates that models trained on satellite data can transfer to real‑flight UAV observations.

By Jiajun Jiang, Chunliang Hua, Zichun Chen, Yanxing Wu, Zeyuan Yang, Jie Song, Xiao Hu
Hugging Face Trending Papers
Jul 22

RIM: A Retrieval-In-Matching Framework for Cross-Domain Global Visual Localization of UAVs

Global visual localization of unmanned aerial vehicles (UAVs) using remote-sensing reference maps has attracted increasing attention. However, acquisition-time and imaging-platform differences between UAV and reference imagery induce substantial cross-domain appearance and viewpoint shifts, challenging robust six-degree-of-freedom (6-DoF) pose estimation.