Frozen vision-language models saturate at about five objects: GeoScope splits views at a measured counting horizon to lift training-free ultra-high-resolution remote sensing QA
Ultra-high-resolution remote sensing question answering has assumed that once the right view is chosen, a vision-language model's counts and directions can be trusted. GeoScope treats the frozen model as a sensor to be calibrated, measures the number of objects it counts reliably in one view (about five for most models on DOTA aerial images), splits only views beyond that horizon, and computes directions explicitly from grounded boxes. Without training it raises Qwen3-VL-8B by 16.3 and 10.5 points on XLRS-Bench regional counting and spatial relations, and by 16.8 and 36.2 points on UHR-Micro global and regional counting.