Research map / Continual learning / Class-incremental
Class Similarity Weighted Knowledge Distillation for Continual Semantic Segmentation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use class-similarity-weighted knowledge distillation instead of normal knowledge distillation (ablation) | REMINDER · Pascal-VOC 2012 15-1 | all mIoU (%): 23.69 -> 58.52 | Helped |
| Use class-similarity-weighted knowledge distillation instead of UNKD (ablation) | REMINDER · Pascal-VOC 2012 15-1 | all mIoU (%): 50.29 -> 58.52 | Helped |
| Add CSW-KD to the output-distillation objective (ablation) | REMINDER · Pascal-VOC 2012 15-1 | avg mIoU (%): 62.47 -> 68.27 | Helped |
| Use REMINDER rather than PLOP | continual semantic segmentation · Pascal-VOC 2012 15-1 | all mIoU (%): 54.68 -> 58.52 | Helped |
| Use REMINDER rather than PLOP | continual semantic segmentation · Pascal-VOC 2012 15-1 | new-class mIoU (%): 26.76 -> 27.23 | Helped |
| Use REMINDER rather than PLOP | continual semantic segmentation · ADE20k 100-10 | all mIoU (%): 30.52 -> 33.11 | Helped |
| Use REMINDER rather than PLOP | continual semantic segmentation · ADE20k 100-10 | avg mIoU (%): 34.48 -> 37.47 | Helped |
| Use REMINDER rather than PLOP | continual semantic segmentation · ADE20k 50-50 | all mIoU (%): 29.41 -> 29.39 | No clear effect |
Closest papers by meaning
- Beyond Background Shift: Rethinking Instance Replay in Continual Semantic Segmentation (CVPR 2025 · similarity 0.91)
- TIKP: Text-to-Image Knowledge Preservation for Continual Semantic Segmentation (AAAI 2024 · similarity 0.89)
- Adaptive Prototype Replay for Class Incremental Semantic Segmentation (AAAI 2025 · similarity 0.88)
- Continual Segmentation with Disentangled Objectness Learning and Class Recognition (CVPR 2024 · similarity 0.88)
- Attacks on Continual Semantic Segmentation by Perturbing Incremental Samples (AAAI 2024 · similarity 0.88)
- Enhancing Visual Continual Learning with Language-Guided Supervision (CVPR 2024 · similarity 0.87)
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