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ProNet: Learning to Propose Object-Specific Boxes for Cascaded Neural Networks

CVPR 2016 · Detection and segmentation › Weakly supervised detection and segmentation · approach: Weakly supervised object localization · 61 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use LSE pooling instead of max pooling (ablation)ProNet proposal network · PASCAL VOC 2012 valclassification mAP: 83.4 -> 84.8Helped
Use LSE pooling instead of average pooling (ablation)ProNet proposal network · PASCAL VOC 2012 valclassification mAP: 81.1 -> 84.8Helped
Use LSE pooling instead of max pooling (ablation)ProNet proposal network · PASCAL VOC 2012 vallocalization mAP: 72.5 -> 74.8Helped
Use LSE pooling instead of average pooling (ablation)ProNet proposal network · PASCAL VOC 2012 vallocalization mAP: 62.8 -> 74.8Helped
Add a verification network after proposal generation (ablation)ProNet · PASCAL VOC 2012 valclassification mAP: 67.8 -> 69.2Helped
Add a verification network after proposal generation (ablation)ProNet · PASCAL VOC 2012 vallocalization mAP: 43.5 -> 45.4Helped
Add a second cascade trained using additional MS COCO data (ablation)ProNet cascade · PASCAL VOC 2012 valclassification mAP: 88.1 -> 89.0Helped
Add a second cascade trained using additional MS COCO data (ablation)ProNet cascade · PASCAL VOC 2012 vallocalization mAP: 77.7 -> 78.5Helped
Use tree-structured category-domain branches instead of a chain (ablation)ProNet cascade · MS COCO valclassification mAP: 69.2 -> 70.9Helped
Use tree-structured category-domain branches instead of a chain (ablation)ProNet cascade · MS COCO vallocalization mAP: 45.4 -> 46.4Helped
Pass more top-scoring proposals to verification, increasing k from 1 to 3 per scale (ablation)ProNet cascade · PASCAL VOC 2012 valclassification mAP: 87.7 -> 88.1Helped
Pass more top-scoring proposals to verification, increasing k from 1 to 3 per scale (ablation)ProNet cascade · PASCAL VOC 2012 vallocalization mAP: 76.3 -> 77.1Helped

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