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C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object Detection

CVPR 2019 · Detection and segmentation › Weakly supervised detection and segmentation · approach: Weakly supervised detection · 263 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace MIL with continuation instance selection and detector estimationMIL on PASCAL VOC 2007 with VGGF · PASCAL VOC 2007mAP: 36.0 vs. 40.7Helped
Use continuation instance selection only (ablation)C-MIL on PASCAL VOC 2007 with VGGF · PASCAL VOC 2007mAP: 36.0 vs. 39.0Helped
Use continuation object estimation only (ablation)C-MIL on PASCAL VOC 2007 with VGGF · PASCAL VOC 2007mAP: 36.0 vs. 37.4Helped
Combine continuation instance selection and object estimation (ablation)C-MIL on PASCAL VOC 2007 with VGGF · PASCAL VOC 2007mAP: 40.7% vs. 36.0%Helped
Use the Log continuation function rather than the other tested schedules (ablation)C-MIL on PASCAL VOC 2007 with VGGF · PASCAL VOC 2007mAP: 37.9, 37.6, 38.3, 37.1 -> 40.7Helped
Use the Log continuation function rather than the other tested schedules (ablation)C-MIL on PASCAL VOC 2007 with VGGF · PASCAL VOC 2007CorLoc: 58.9, 57.4, 58.4, 56.4 -> 59.5Helped
Apply C-MIL instead of MELMWeakly supervised detection with VGGF · PASCAL VOC 2007 testmAP: 40.7% vs. 38.4%Helped
Apply C-MIL instead of MELMWeakly supervised detection with VGG16 · PASCAL VOC 2007 testmAP: 50.5% vs. 47.3%Helped
Apply C-MIL instead of MELMWeakly supervised detection with VGG16 · PASCAL VOC 2012mAP: 46.7% vs. 42.4%Helped
Apply C-MIL instead of WeakRPNWeakly supervised localization with VGG16 · PASCAL VOC 2012CorLoc: 67.4% vs. 64.9%Helped
Apply C-MIL instead of WeakRPNObject localization with VGG16 · PASCAL VOC 2007 trainvalmAP: 65.0% vs. 63.8%Helped

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