SATS: Self-attention transfer for continual semantic segmentation

•Propose distilling self-attention maps for continual semantic segmentation.•Propose a class-specific region pooling for relational knowledge transfer.•First study to innovatively apply Transformer to continual semantic segmentation.•Can flexibly combine the proposed method with existing strategies.•Extensive evaluation on multiple benchmarks and settings with SOTA performance.