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Despite significant progress in global localization of Unmanned Aerial Vehicles (UAVs) in GPS-denied environments, existing methods remain constrained by the availability of datasets. Current datasets often focus on small-scale scenes and lack viewpoint variability, accurate ground truth (GT) pose, and UAV build-in sensor data. To address these limitations, we introduce a large-scale 6-DoF UAV dataset for localization (UAVD4L) and develop a two-stage 6-DoF localization pipeline (UAVLoc), which consists of offline synthetic data generation and online visual localization. Additionally, based on the 6DoF estimator, we design a hierarchical system for tracking ground target in 3 D space. Experimental results on the new dataset demonstrate the effectiveness of the proposed approach. Code and dataset are available at https: //github. com/RingoWRW/UAVD4L.
Wu et al. (Mon,) studied this question.
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