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Research map / Point clouds / Shape and surface completion

Variational Relational Point Completion Network

CVPR 2021 · Point clouds › Shape and surface completion · approach: Point cloud completion networks · 237 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use VRCNet instead of ECGPoint cloud completion · MVP, 16,384 pointsCD ×10^4: 3.58 -> 3.06Helped
Use VRCNet instead of NSFAPoint cloud completion · MVP, 16,384 pointsF-Score@1%: 0.783 -> 0.796Helped
Use VRCNet instead of GRNetPoint cloud completion · Completion3D, 2,048 pointsCD ×10^4: 10.64 -> 8.12Helped
Add Point Self-Attention to the ECG baseline (ablation)ECG · MVP, 2,048 pointsCD ×10^4: 6.64 -> 6.35Helped
Add Point Self-Attention to the ECG baseline (ablation)ECG · MVP, 2,048 pointsF1: 0.476 -> 0.484Helped
Add dual-path architecture to the ECG baseline (ablation)ECG · MVP, 2,048 pointsCD ×10^4: 6.64 -> 6.43Helped
Add dual-path architecture to the ECG baseline (ablation)ECG · MVP, 2,048 pointsF1: 0.476 -> 0.488Helped
Add dual-path architecture and kernel selection, without PSA (ablation)ECG · MVP, 2,048 pointsCD ×10^4: 6.64 -> 6.35Helped
Add dual-path architecture and kernel selection, without PSA (ablation)ECG · MVP, 2,048 pointsF1: 0.476 -> 0.490Helped
Add PSA and dual-path architecture, without kernel selection (ablation)ECG · MVP, 2,048 pointsCD ×10^4: 6.64 -> 6.15Helped
Add PSA and dual-path architecture, without kernel selection (ablation)ECG · MVP, 2,048 pointsF1: 0.476 -> 0.492Helped
Add PSA, dual-path architecture, and kernel selection (ablation)ECG · MVP, 2,048 pointsCD ×10^4: 6.64 -> 5.96Helped

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