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Bridging the Gap between Object and Image-level Representations for Open-Vocabulary Detection

NeurIPS 2022 · Detection and segmentation › Open-set and few-shot detection · approach: Open-vocabulary object detection · 69 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add RKD to the supervised detector (ablation)COCO detector · COCOAP_novel: 1.7 -> 21.2Helped
Add pseudo-box image-level supervision (ablation)COCO detector · COCOAP_novel: 1.7 -> 30.4Helped
Combine RKD and PIS without weight transfer (ablation)COCO detector · COCOAP_novel: 30.4 -> 31.5Helped
Add weight transfer to RKD + PIS (ablation)COCO detector · COCOAP_novel: 31.5 -> 36.6Helped
Use MViT rather than RPN proposals for L1 distillation (ablation)COCO detector · COCOAP_novel: 4.0 -> 16.7Helped
Add IRM to L1 distillation (ablation)COCO detector · COCOAP_novel: 16.7 -> 21.2Helped
Use class-specific MViT proposals instead of max-size MViT proposals for ILS (ablation)COCO detector · COCOAP_novel: 28.9 -> 30.4Helped
Initialize RKD from the supervised-base detector rather than training from scratch (ablation)COCO detector · COCOAP_base: 50.9 -> 54.7Helped
Remove the MLP skip connection from weight transfer (ablation)Ours · COCOAP_novel: 36.6 -> 32.5Hurt
Remove the MLP skip connection from weight transfer (ablation)Ours · LVISAP_r: 17.1 -> 18.1Mixed
Use weight transfer rather than naively combining RKD and PIS (ablation)LVIS detector · LVISAP: 22.1 -> 22.8Helped
Use class-specific MViT proposals rather than max-score RPN proposals for ILS (ablation)LVIS detector · LVISAP_r: 12.8 -> 17.0Helped

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