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D$^2$CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropouts

NeurIPS 2023 · 3D vision › Face and shape · approach: Primitive-based shape abstraction · 4 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add complementary primitives (ablation)CAPRI-Net baseline · ABCCD: 0.177 -> 0.073Helped
Add complementary primitives (ablation)CAPRI-Net baseline · ABC#P: 66 -> 38Helped
Add dual branches on top of complementary primitives (ablation)D2CSG · ABCCD: 0.073 -> 0.069Helped
Add dual branches on top of complementary primitives (ablation)D2CSG · ABC#P: 38 -> 53Hurt
Add dropout in final stage on top of CP+DB (ablation)D2CSG · ABC#P: 53 -> 29Helped
Add dropout in final stage on top of CP+DB (ablation)D2CSG · ABCCD: 0.069 -> 0.069No clear effect
Add dropout in final stage on top of CP+DB (ablation)D2CSG · ABCNC: 0.936 -> 0.928Hurt
Replace dual branching by dropout (CP+DO vs CP+DB) (ablation)D2CSG · ABCCD: 0.069 -> 0.088Hurt
Add dropout to CP only (no dual branch) (ablation)D2CSG · ABC#P: 38 -> 27Helped
Add dropout to CP only (no dual branch) (ablation)D2CSG · ABCCD: 0.073 -> 0.088Hurt
Full D2CSG vs CAPRI-Net on mesh input (ablation)D2CSG · ABCCD: 0.177 -> 0.069Helped
Full D2CSG vs CAPRI-Net on mesh input (ablation)D2CSG · ShapeNetNC: 0.890 -> 0.887Hurt

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