Introduces the first billion-scale SAR vision foundation model and a massive unified benchmark for all-weather geospatial semantic segmentation.
arXiv · March 13, 2026 · 2603.12008
Why it matters
Synthetic Aperture Radar (SAR) is crucial for all-weather earth observation but suffers from severe domain shifts; this billion-scale release democratizes high-performance SAR analysis and provides a new standard for cross-sensor generalization.
From the abstract
Synthetic Aperture Radar (SAR) enables global, all-weather earth observation. However, owing to diverse imaging mechanisms, domain shifts across sensors and regions severely hinder its semantic generalization. To address this, we present CrossEarth-SAR, the first billion-scale SAR vision foundation model built upon a novel physics-guided sparse mixture-of-experts (MoE) architecture incorporating physical descriptors, explicitly designed for cross-domain semantic segmentation. To facilitate large