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Skeleton-bridged Point Completion: From Global Inference to Local Adjustment

NeurIPS 2020 · Point clouds › Shape and surface completion · approach: Point cloud completion networks · 39 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use skeleton-bridged completion instead of the strongest listed point-completion baselineSK-PCN · ShapeNetCore test (average)CD-L2 (×1000): 0.228 -> 0.175Helped
use skeleton-bridged completion instead of the strongest listed point-completion baselineSK-PCN · ShapeNetCore test (average)EMD (×100): 0.591 -> 0.499Helped
use skeleton-bridged completion instead of the strongest listed mesh baselineSK-PCN · ShapeNetCore mesh completion (average)CD-L2 (×1000): 0.222 -> 0.152Helped
use skeleton-bridged completion instead of the strongest listed mesh baselineSK-PCN · ShapeNetCore mesh completion (average)Normal Consistency: 0.834 -> 0.872Helped
add Non-Local Attention (ablation)SK-PCN · ShapeNetCore testCD: 0.340 -> 0.205Helped
add Surface Adjustment (ablation)SK-PCN · ShapeNetCore testCD_acc: 0.326 -> 0.248Helped
add Non-Local Attention and Surface Adjustment (ablation)SK-PCN · ShapeNetCore testCD: 0.340 -> 0.175Helped
replace skeletal-point bridge with 2,048 coarse surface points (ablation)SK-PCN · ChairCD: 1.59e-4 -> 2.96e-4Hurt
replace skeletal-point bridge with 2,048 coarse surface points (ablation)SK-PCN · ChairNormal Consistency: 0.86 -> 0.81Hurt

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