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CasFusionNet: A Cascaded Network for Point Cloud Semantic Scene Completion by Dense Feature Fusion

AAAI 2023 · Point clouds › Segmentation and detection · approach: Scene completion and instance segmentation · 18 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Omit final-level FPSCasFusionNet · SSC-PCCD: 0.70 -> 0.67Helped
Omit final-level FPSCasFusionNet · NYUCAD-PCCD: 10.28 -> 9.99Helped
Omit final-level FPSCasFusionNet · SSC-PCmIoU: 91.3 -> 91.2No clear effect
Omit final-level FPSCasFusionNet · NYUCAD-PCmAcc: 59.7 -> 59.8No clear effect
Add LRM and SSM to all levels (ablation)CasFusionNet · NYUCAD-PCCD: 10.73 -> 10.28Helped
Add LRM to all levels (ablation)CasFusionNet · NYUCAD-PCCD: 10.50 -> 10.28Helped
Add LRM to all levels (ablation)CasFusionNet · NYUCAD-PCmIoU: 49.0 -> 49.5Helped
Add feature fusion between GCM and SSM (ablation)CasFusionNet · NYUCAD-PCCD: 10.61 -> 10.28Helped
Add feature fusion between GCM and SSM (ablation)CasFusionNet · NYUCAD-PCmIoU: 40.3 -> 49.5Helped
Add feature fusion between GCM and SSM (ablation)CasFusionNet · NYUCAD-PCmAcc: 51.9 -> 59.8Helped
Use levels #2 and #3 (ablation)CasFusionNet · NYUCAD-PCCD: 11.60 -> 10.28Helped
Use levels #2 and #3 (ablation)CasFusionNet · NYUCAD-PCmIoU: 41.5 -> 49.5Helped

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