3D Semantic Segmentation On Scribblekitti

mIoU

Results

Performance results of various models on this benchmark

		Paper Title
IGNet	62.0	2D Feature Distillation for Weakly- and Semi-Supervised 3D Semantic Segmentation
SSLSS with Cylinder3D	61.3	Scribble-Supervised LiDAR Semantic Segmentation
Cylinder3D	57.0	Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation
MinkowskiNet	55.0	4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks
LiM3D	-	Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation
LiM3D+SDSC	-	Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation

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