DSGR
We introduce Domain Shift across Geographic Regions (DSGR), a new large-scale dataset designed to study the effects of real-world geospatial distribution shifts in satellite imagery classification. DSGR captures variability across diverse geographic regions, with particular emphasis on underrepresented areas such as Africa and Oceania, enabling systematic analysis of how regional differences impact model performance. This […]
RWDS
Object detectors achieve strong performance on benchmark datasets, yet most are trained under the i.i.d. assumption, leading to significant degradation when deployed under real-world distribution shifts. Domain Generalisation (DG) addresses this challenge by enabling models to generalise to unseen, Out-Of-Distribution data without access to target domains during training. However, evaluating object detection under realistic DG […]