TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK
Instance Segmentation	NYU Depth v2	SGPN-CNN	mAP@0.5	30.5	# 1
3D Object Detection	NYU Depth v2	SGPN-CNN	MAP	41.3	# 1
3D Semantic Instance Segmentation	ScanNetV1	SGPN	mAP@0.25	35.1	# 1
3D Semantic Instance Segmentation	ScanNetV2	SGPN	mAP@0.50	14.3	# 5
3D Object Detection	ScanNetV2	SGPN	mAP@0.25	20.7	# 8
Semantic Segmentation	ShapeNet	SGPN	Mean IoU	85.8%	# 1
3D Part Segmentation	ShapeNet-Part	SGPN	Class Average IoU	82.8	# 10
3D Part Segmentation	ShapeNet-Part	SGPN	Instance Average IoU	85.8	# 11

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

CVPR 2018 • Weiyue Wang • Ronald Yu • Qiangui Huang • Ulrich Neumann

We introduce Similarity Group Proposal Network (SGPN), a simple and intuitive deep learning framework for 3D object instance segmentation on point clouds. SGPN uses a single network to predict point grouping proposals and a corresponding semantic class for each proposal, from which we can directly extract instance segmentation results... (read more)

PDF Abstract CVPR 2018 PDF CVPR 2018 Abstract

Code

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laughtervv/SGPN official

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Tasks

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3D INSTANCE SEGMENTATION

3D OBJECT DETECTION

3D PART SEGMENTATION

3D SEMANTIC INSTANCE SEGMENTATION

INSTANCE SEGMENTATION

OBJECT DETECTION

SCENE SEGMENTATION

SEMANTIC SEGMENTATION

Datasets

ShapeNet

ScanNet

NYUv2

Results from the Paper

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Ranked #1 on Semantic Segmentation on ShapeNet

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TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK	BENCHMARK
Instance Segmentation	NYU Depth v2	SGPN-CNN	mAP@0.5	30.5	# 1	Compare
3D Object Detection	NYU Depth v2	SGPN-CNN	MAP	41.3	# 1	Compare
3D Semantic Instance Segmentation	ScanNetV1	SGPN	mAP@0.25	35.1	# 1	Compare
3D Semantic Instance Segmentation	ScanNetV2	SGPN	mAP@0.50	14.3	# 5	Compare
3D Object Detection	ScanNetV2	SGPN	mAP@0.25	20.7	# 8	Compare
Semantic Segmentation	ShapeNet	SGPN	Mean IoU	85.8%	# 1	Compare
3D Part Segmentation	ShapeNet-Part	SGPN	Class Average IoU	82.8	# 10	Compare
3D Part Segmentation	ShapeNet-Part	SGPN	Instance Average IoU	85.8	# 11	Compare

Methods used in the Paper

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