Abstract: Self-supervised learning (SSL) has emerged as a promising paradigm for remote sensing semantic segmentation, enabling the exploitation of large-scale unlabeled data to learn meaningful ...

Abstract: Class-incremental semantic segmentation focuses on updating the segmentation model with only new-class samples. Catastrophic forgetting and background shift are the two prevalent challenges.