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Research map / Detection and segmentation / Weakly supervised detection and segmentation

Evaluating Weakly Supervised Object Localization Methods Right

CVPR 2020 · Detection and segmentation › Weakly supervised detection and segmentation · approach: Weakly supervised object localization · 191 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use the best later WSOL method instead of CAMWSOL methods under the shared validation and evaluation protocol · ImageNetMaxBoxAcc: 63.5 -> 63.8Mixed
Use the best later WSOL method instead of CAMWSOL methods under the shared validation and evaluation protocol · CUBMaxBoxAcc: 68.8 -> 70.8Helped
Use the best later WSOL method instead of CAMWSOL methods under the shared validation and evaluation protocol · OpenImagesPxAP: 59.1 -> 59.5Helped
Train a model using the available full-supervision samples instead of using them only for hyperparameter searchFSL baseline versus CAM · ImageNetMaxBoxAcc: 63.5 -> 66.3Helped
Train a model using the available full-supervision samples instead of using them only for hyperparameter searchFSL baseline versus CAM · CUBMaxBoxAcc: 68.8 -> 92.0Helped
Train a model using the available full-supervision samples instead of using them only for hyperparameter searchFSL baseline versus CAM · OpenImagesPxAP: 59.1 -> 68.7Helped
Increase ADL and ACoL erasing thresholds (ablation)ADL and ACoL · Evaluated benchmarkslocalization performanceHelped
Lower ADL and HaS drop rates (ablation)ADL and HaS · Evaluated benchmarkslocalization performanceHelped
Use erasing hyperparameters introduced in methods after CAM (ablation)WSOL methods · Evaluated benchmarkslocalization performanceHurt

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