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

Weakly Supervised Video Salient Object Detection

CVPR 2021 · Detection and segmentation › Weakly supervised detection and segmentation · approach: Weakly supervised detection · 90 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add optical flow with the proposed appearance-motion fusion module (ablation)B RGB-only baseline · DAVSODFβ: 0.543 -> 0.562Helped
use proposed appearance-motion fusion instead of element-wise addition (ablation)B-Fa · DAVSODFβ: 0.556 -> 0.562Helped
use proposed appearance-motion fusion instead of concatenation (ablation)B-Fc · FBMSFβ: +2%Helped
add TIEM at every feature level rather than only the highest level (ablation)B-Fo · DAVSODMAE: 0.121 -> 0.108Helped
add foreground-background similarity loss (ablation)B-Fo-Ta · DAVSODFβ: 0.585 -> 0.605Helped
use GraphCut to convert scribbles into training masks (ablation)B · DAVSODFβ: 0.543 -> 0.424Hurt
apply saliency boostingOurs · DAVSODFβ: 0.605 -> 0.593Hurt
apply saliency boostingOurs · FBMSSα: 0.778 -> 0.803Helped
apply saliency boostingOurs · DAVISSα: 0.828 -> 0.846Helped
apply saliency boostingOurs · VOSSα: 0.750 -> 0.765Helped
apply saliency boostingOurs · SegV2Sα: 0.804 -> 0.819Helped
apply saliency boostingOurs · ViSalSα: 0.857 -> 0.883Helped

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