Semantic Segmentation On Scannet

Metriken

test mIoU

val mIoU

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	test mIoU	val mIoU	Paper Title	Repository
LSK3DNet	75.5	75.7	LSK3DNet: Towards Effective and Efficient 3D Perception with Large Sparse Kernels
MSC + SparseUNet	-	75.5	Masked Scene Contrast: A Scalable Framework for Unsupervised 3D Representation Learning
FCPN	44.7	-	Fully-Convolutional Point Networks for Large-Scale Point Clouds
Tangent Convolutions	44.2	-	Tangent Convolutions for Dense Prediction in 3D
BFANet	-	78.0	-	-
PTv2	75.2	75.4	Point Transformer V2: Grouped Vector Attention and Partition-based Pooling
PointCNN	45.8	-	PointCNN: Convolution On X-Transformed Points
Serialized Piont Mamba	-	76.8	Serialized Point Mamba: A Serialized Point Cloud Mamba Segmentation Model	-
TextureNet	56.6	-	TextureNet: Consistent Local Parametrizations for Learning from High-Resolution Signals on Meshes
FG-Net	69.0	-	FG-Net: Fast Large-Scale LiDAR Point Clouds Understanding Network Leveraging Correlated Feature Mining and Geometric-Aware Modelling
OctFormer	76.6	75.7	OctFormer: Octree-based Transformers for 3D Point Clouds
3DMV	48.4	-	3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation
PointNet++	33.9	53.5	PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
KPConvX-L	-	76.3	KPConvX: Modernizing Kernel Point Convolution with Kernel Attention	-
BPNet	74.9	73.9	Bidirectional Projection Network for Cross Dimension Scene Understanding
StratifiedFormer	73.7	74.3	Stratified Transformer for 3D Point Cloud Segmentation
PPT + SparseUNet	76.6	76.4	Towards Large-scale 3D Representation Learning with Multi-dataset Point Prompt Training
OneFormer3D	-	76.6	OneFormer3D: One Transformer for Unified Point Cloud Segmentation
PTv3 ARKit LabelMaker	79.8	79.1	ARKit LabelMaker: A New Scale for Indoor 3D Scene Understanding
AVS-Net	-	76.1	AVS-Net: Point Sampling with Adaptive Voxel Size for 3D Scene Understanding

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