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Relation Networks for Object Detection

CVPR 2018 · Detection and segmentation › CNN features · approach: Local features and context in CNNs · 1,559 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add relation modules to the instance-recognition headFaster R-CNN, ResNet-101 · COCO minivalmAP: 32.2 -> 34.7Helped
Add relation modules to the instance-recognition headFPN, ResNet-101 · COCO minivalmAP: 36.8 -> 38.1Helped
Add relation modules to the instance-recognition headDCN, ResNet-101 · COCO minivalmAP: 37.5 -> 38.1Helped
Train instance recognition and duplicate removal end-to-endFaster R-CNN + relation modules · COCO minivalmAP: 30.5 -> 31.0Helped
Use pairwise geometric attention weights instead of no geometry or unary geometry (ablation)Relation module · COCO minivalmAP: 30.3, 31.1 -> 31.9Helped
Increase relation count from 1 to 16 (ablation)Relation module · COCO minivalmAP: 30.5 -> 31.9Helped
Increase relation-module count from {1,1} to {4,4} (ablation)2fc+RM head · COCO minivalmAP: 31.9 -> 32.8Helped
Replace relation modules with a wider 2fc head (ablation)Faster R-CNN head · COCO minivalmAP: 29.6 -> 29.7No clear effect
Replace relation modules with a deeper 3fc head (ablation)Faster R-CNN head · COCO minivalmAP: 29.6 -> 29.0Hurt
Add global context features without relation modules (ablation)2fc head · COCO minivalmAP: 29.6 -> 29.6No clear effect
Add larger-window context features (ablation)2fc head · COCO minivalmAP: 29.6 -> 30.4Helped
Remove rank feature (ablation)Duplicate removal network · COCO minivalmAP: 30.3 -> 26.6Hurt

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