Research map / Continual learning / Class-incremental
Saving 100x Storage: Prototype Replay for Reconstructing Training Sample Distribution in Class-Incremental Semantic Segmentation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add prototype replay (ablation) | STAR · VOC 2012 overlapped 15-1 | mIoU all: 70.3 -> 72.6 | Helped |
| add background repetition (ablation) | STAR · VOC 2012 overlapped 15-1 | mIoU all: 68.1 -> 72.6 | Helped |
| add OCFM loss (ablation) | STAR · VOC 2012 overlapped 15-1 | mIoU all: 31.4 -> 72.6 | Helped |
| add SAD loss (ablation) | STAR · VOC 2012 overlapped 15-1 | mIoU all: 71.6 -> 72.6 | Helped |
| prototype replay instead of 100 stored raw images (DKD-M) | STAR vs DKD-M · ADE20K overlapped 100-50 | mIoU all: 36.0 -> 36.4 | Helped |
| add 50 raw images to STAR | STAR · VOC 2012 overlapped 15-1 | mIoU all: 72.6 -> 73.8 | Helped |
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