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SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation

CVPR 2018 · Point clouds › Segmentation and detection · approach: Point cloud semantic segmentation · 598 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use SGPN similarity-based group proposals instead of semantic clusteringS3DIS instance segmentation · S3DISmean AP at IoU 0.5: 17.40 -> 36.30Helped
use SGPN group proposals instead of semantic clusteringS3DIS instance segmentation · S3DISmean AP at IoU 0.25: 34.8 -> 52.6Helped
use SGPN group proposals instead of semantic clusteringS3DIS instance segmentation · S3DISmean AP at IoU 0.75: 11.2 -> 18.8Helped
derive detections from SGPN instance groups rather than PointNet detectionsS3DIS 3D detection · S3DISmean AP at IoU 0.5: 24.24 -> 30.20Helped
add the similarity-matrix branch to the semantic segmentation frameworkSGPN · S3DISmean IoU (%): 49.76 -> 50.37Helped
add 2D CNN features from RGB images (ablation)SGPN · NYUV2 instance segmentationmean AP at IoU 0.5: 26.5 -> 30.5Helped
add 2D CNN features from RGB images (ablation)SGPN · NYUV2 3D detectionmean AP: 36.25 -> 41.30Helped
add the similarity-matrix branch to the PointNet++ semantic segmentation baselineSGPN · ShapeNet part segmentationmean IoU (%): 84.6 -> 85.8Helped
use SGPN group proposals instead of semantic clusteringSGPN · ScanNet(v1) instance segmentationmean AP at IoU 0.25: 32.5 -> 35.1Helped
add 2D CNN features from RGB images (ablation)SGPN · NYUV2 instance segmentationAP by category: 55.9 -> 56.4; 59.6 -> 50.6Mixed

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