3D Semantic Segmentation On Sensaturban

Metrics

mIoU

Results

Performance results of various models on this benchmark

		Paper Title
LCPFormer	63.4	LCPFormer: Towards Effective 3D Point Cloud Analysis via Local Context Propagation in Transformers
EyeNet	62.30	Human Vision Based 3D Point Cloud Semantic Segmentation of Large-Scale Outdoor Scene
BEV-Seg3D-Net	61.7	Efficient Urban-scale Point Clouds Segmentation with BEV Projection
KPConv	57.58	KPConv: Flexible and Deformable Convolution for Point Clouds
SCF-Net	55.1	SCF-Net: Learning Spatial Contextual Features for Large-Scale Point Cloud Segmentation
SparseConv	42.66	3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
SPGraph	37.29	Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs
TangentConv	33.30	Tangent Convolutions for Dense Prediction in 3D

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3D Semantic Segmentation On Sensaturban | SOTA | HyperAI