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Attentive Feedback Network for Boundary-Aware Salient Object Detection

CVPR 2019 · Detection and segmentation › CNN features · approach: RGB salient object detection · 517 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use AFNet instead of PiCANetsalient object detection · DUTS-testFmaxβ: .851 -> .862Helped
Use AFNet instead of the strongest listed baselinesalient object detection · ECSSDFmaxβ: .931 -> .935Helped
Use AFNet instead of PiCANetsalient object detection · PASCAL-SFmaxβ: .868 -> .868No clear effect
Use AFNet instead of PiCANetsalient object detection · DUT-OMRONFmaxβ: .794 -> .797Helped
Use AFNet instead of PiCANetsalient object detection · HKU-ISFmaxβ: .921 -> .923Helped
Add ternary-attention feedback through AFMs (ablation)AFNet · DUTS-testFmaxβ: .8586 -> .8624Helped
Add Boundary-Enhanced Loss (ablation)AFNet · DUTS-testFmaxβ: .8557 -> .8624Helped
Use multi-scale GPMs rather than a single global module (ablation)AFNet global saliency prediction · DUTS-testFmaxβ: .787 -> .791Helped
Replace fully-connected global prediction with GPM (ablation)AFNet global saliency prediction · DUTS-testFmaxβ: .769 -> .791Helped
Replace dilated convolution global prediction with GPM (ablation)AFNet global saliency prediction · DUTS-testFmaxβ: .779 -> .791Helped
Replace pyramid pooling global prediction with GPM (ablation)AFNet global saliency prediction · DUTS-testFmaxβ: .781 -> .791Helped

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