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Research map / Detection and segmentation / CNN features

Structure-Aware Image Segmentation with Homotopy Warping

NeurIPS 2022 · Detection and segmentation › CNN features · approach: Context modeling for semantic segmentation · 7 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add homotopy warping loss to UNetUNet · RoadTracerBetti error: 1.591 -> 1.251Helped
add homotopy warping loss to 3D UNet3D UNet · CREMIDICE: 0.961 -> 0.967 (DMT 0.973)Mixed
warping loss vs DMT on Mass. ARIHomotopy Warping · Mass.ARI: 0.881 (DMT) vs 0.864Hurt
use distance-transform ordering when warping (ablation)Homotopy Warping · RoadTracerBetti error: 1.473 -> 1.251Helped
warp in both directions instead of GT->Pred only (ablation)Homotopy Warping · RoadTracerARI: 0.567 -> 0.572Helped
use cross-entropy instead of MSE as pixel loss in L_warp (ablation)Homotopy Warping · RoadTracerBetti error: 1.429 -> 1.251Helped
use cross-entropy instead of Dice as pixel loss in L_warp (ablation)Homotopy Warping · RoadTracerDICE: 0.606 (Dice loss) vs 0.603 (CE)Hurt
vary lambda_warp from 2e-5 to 2e-4 (ablation)Homotopy Warping · RoadTracerBetti error: best 1.251 at 1e-4; 1.412 at 5e-5Mixed
add warping loss instead of morphological closing post-processing (ablation)UNet · RoadTracerBetti error: 1.583 -> 1.251Helped
apply morphological closing post-processing to UNet (ablation)UNet · RoadTracerBetti error: 1.591 -> 1.590No clear effect

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