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Research map / Detection and segmentation / CNN features

Deep Embedding Features for Salient Object Detection

AAAI 2019 · Detection and segmentation › CNN features · approach: RGB salient object detection · 41 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add Feature Embedding Network (FEN) to baseline (ablation)DEF saliency network · ECSSDF-measure: 0.821 -> 0.874Helped
add FEN to baseline (ablation)DEF saliency network · DUTS-TEF-measure: 0.721 -> 0.763Helped
add FEN to baseline (ablation)DEF saliency network · ECSSDMAE: 0.055 -> 0.046Helped
add recursive feature integration (RFIN stage-4) over FEN (ablation)DEF saliency network · ECSSDF-measure: 0.874 -> 0.905Helped
add recursive feature integration (RFIN stage-4) over FEN (ablation)DEF saliency network · DUTS-TEF-measure: 0.763 -> 0.813Helped
add recursive feature integration (RFIN stage-4) over FEN (ablation)DEF saliency network · DUTS-TEMAE: 0.067 -> 0.046Helped
add Guided Filter Refinement Network (GFRN) (ablation)DEF saliency network · ECSSDF-measure: 0.905 -> 0.915Helped
add GFRN (ablation)DEF saliency network · DUTS-TEF-measure: 0.813 -> 0.821Helped
add GFRN (ablation)DEF saliency network · ECSSDMAE: 0.037 -> 0.036Helped
use ResNet-101 instead of VGG-16 backbone (ablation)DEF saliency network · ECSSDF-measure: 0.889 -> 0.915Helped
use ResNet-101 instead of DenseNet-161 backbone (ablation)DEF saliency network · DUTS-TEF-measure: 0.792 -> 0.821Helped

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