WideUAV: Cross-View Satellite-Tile Retrieval and Target-Extent Grounding

In wide-area satellite imagery, finding the matching tile is only the first step toward localizing a target observed from a UAV: the target must also be grounded within that tile. We study cross-view geo-grounding, a unified setting that combines satellite-tile retrieval with target grounding. To support this task, We introduce WideUAV, a rendered benchmark comprising 3,505 wide satellite tiles annotated with off-centered target bounding boxes and 112,160 UAV queries captured under controlled variations in altitude and heading. In contrast to existing cross-view benchmarks such as University-1652, where satellite images are tightly cropped to 120m × 120m around the target, WideUAV uses 2370m × 1328m satellite images, covering over 200× the area. The drone-view queries are sampled at 32 views per location on a fixed grid of 4 altitudes and 8 headings. We further propose UNISAG (Unified Satellite Retrieval and Grounding), a single model that shares visual representations across retrieval and grounding while incorporating UAV heading and altitude cues. To jointly evaluate retrieval and grounding, we introduce retrieval-gated uIoU, an end-to-end metric that assigns zero uIoU when the correct satellite tile is not retrieved. On this metric, UNISAG achieves 22.67%, outper- forming several competitive re-implemented approaches, including TransGeo, with an 18.87-point gain over the strongest baseline at 3.80%. We also observe an asymmetric interaction between the two parts: grounding supervision improves the retrieval representation, whereas retrieval supervision improve little to grounding.