Semantic Segmentation On Toronto 3D L002

mIoU

Results

Performance results of various models on this benchmark

		Paper Title
EyeNet	81.13	Human Vision Based 3D Point Cloud Semantic Segmentation of Large-Scale Outdoor Scene
RandLA-Net	74.3	RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds
CLOUDSPAM	71.8	CLOUDSPAM: Contrastive Learning On Unlabeled Data for Segmentation and Pre-Training Using Aggregated Point Clouds and MoCo
DA-supervised	69.3	CLOUDSPAM: Contrastive Learning On Unlabeled Data for Segmentation and Pre-Training Using Aggregated Point Clouds and MoCo
PointNet++	56.5	PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

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