Die-Die Liu

RACL: reliability-aware contrastive learning for weakly supervised change detection

Weakly supervised change detection aims to identify land-cover changes from bi-temporal remote sensing images using limited annotations. However, relying solely on image-level supervision often leads to inaccurate change localization and noisy pseudo-labels. To address this issue, we propose an end-to-end framework for...