Semi-Supervised Building Change Detection From Bitemporal Remote Sensing Images Leveraging Visual–Language Models and Consistency Learning (opens in new tab)

Building change detection (CD) from bitemporal remote sensing images aims to identify newly constructed, demolished, or modified buildings by comparing observations acquired at different times. A major limitation of existing supervised approaches is their strong dependence on pixelwise building and change annotations, which are costly and labor-intensive to obtain at scale. To address this challenge, we propose SemiBCD, a semi-supervised framework that integrates visual–language model (VLM) p...