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Incremental-DETR: Incremental Few-Shot Object Detection via Self-Supervised Learning

AAAI 2023 · Detection and segmentation › Open-set and few-shot detection · approach: Few-shot object detection · 60 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use Incremental-DETR rather than iMTFAincremental few-shot detection · COCO val, 5-shot, all classesAP: 19.6 -> 24.9Helped
Use Incremental-DETR rather than iMTFAincremental few-shot detection · COCO val, 10-shot, all classesAP: 19.3 -> 24.1Helped
Use Incremental-DETR rather than ONCEincremental few-shot detection · VOC test, 5-shot, novel classesAP: 2.4 -> 16.6Helped
Add the two-stage fine-tuning, self-supervised losses, and distillation components (ablation)Incremental-DETR · COCO val, 5-shot, all classesAP: 0.4 -> 24.9Helped
Add the self-supervised box and classification losses (ablation)Incremental-DETR with two-stage fine-tuning · COCO val, 5-shot, novel classesAP: 5.2 -> 8.0Helped
Add feature distillation (ablation)Incremental-DETR with self-supervised losses and classification distillation · COCO val, 5-shot, all classesAP: 21.6 -> 24.9Helped
Add classification distillation (ablation)Incremental-DETR with self-supervised losses and feature distillation · COCO val, 5-shot, all classesAP: 19.9 -> 24.9Helped
Use two-step rather than one-step base pre-training (ablation)Incremental-DETR · COCO val, 5-shot, novel classesAP: 7.1 -> 8.3Helped
Keep class-agnostic modules frozen during novel-class fine-tuning (ablation)Incremental-DETR · COCO val, 5-shot, all classesAP: 4.1 -> 24.9Helped

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