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Research map / Detection and segmentation / CNN features

Gated Fully Fusion for Semantic Segmentation

AAAI 2020 · Detection and segmentation › CNN features · approach: Context modeling for semantic segmentation · 185 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace ungated feature fusion with GFF (ablation)PSPNet · Cityscapes validationmIoU: 78.6 -> 80.4Helped
Use concatenation for feature fusion instead of the PSPNet baseline (ablation)PSPNet · Cityscapes validationmIoU: 78.6 -> 78.8 (0.2↑)Helped
Use addition for feature fusion instead of the PSPNet baseline (ablation)PSPNet · Cityscapes validationmIoU: 78.6 -> 78.7 (0.1↑)Helped
Add gates to the FPN top-down pathway (ablation)PSPNet + FPN · Cityscapes validationmIoU: 79.3 -> 79.4 (0.8 ↑)Helped
Add DFP after GFF (ablation)PSPNet + GFF · Cityscapes validationmIoU: 80.4 -> 81.2 (2.6↑)Helped
Use multi-scale inference (ablation)PSPNet + GFF + DFP · Cityscapes validationmIoU: 81.2 -> 81.8 (3.2↑)Helped
Add GFF to DenseASPP (ablation)DenseASPP · Cityscapes validationmIoU: 78.9 -> 80.1(1.2↑)Helped
Add DFP to DenseASPP + GFF (ablation)DenseASPP + GFF · Cityscapes validationmIoU: 80.1(1.2↑) -> 80.9(2.0↑)Helped
Add GFF to PSP (ablation)PSP with ResNet18 · Cityscapes validationmIoU: 73.0 -> 76.6 (3.6↑)Helped
Add DFP to PSP + GFF (ablation)PSP with ResNet18 · Cityscapes validationmIoU: 76.6 (3.6↑) -> 78.9 (5.9↑)Helped
Apply GFF (ablation)DenseASPP · Cityscapes validationmIoU: 78.9 -> 80.1(1.2↑)Helped

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