Efficient Geometry-Controlled High-Resolution Satellite Image Synthesis

ArXi:2605.04557v1 Announce Type: cross High-resolution satellite images are often scarce and costly, especially for remote areas or infrequent events. This shortage hampers the development and testing of machine learning models for land-cover classification, change detection, and disaster monitoring. In this paper, we tackle the problem of geometry-controlled high-resolution satellite image synthesis by adding control over existing pre-trained diffusion models.