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SOTA
Lidar Semantic Segmentation
Lidar Semantic Segmentation On Paris Lille 3D
Lidar Semantic Segmentation On Paris Lille 3D
평가 지표
mIOU
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
mIOU
Paper Title
Repository
ConvPoint
0.759
ConvPoint: Continuous Convolutions for Point Cloud Processing
GeomGCNN
0.785
Exploiting Local Geometry for Feature and Graph Construction for Better 3D Point Cloud Processing with Graph Neural Networks
-
Feature Geometric Net (FG Net)
0.819
FG-Net: Fast Large-Scale LiDAR Point Clouds Understanding Network Leveraging Correlated Feature Mining and Geometric-Aware Modelling
Paris-Lille-3D
0.31
Paris-Lille-3D: a large and high-quality ground truth urban point cloud dataset for automatic segmentation and classification
-
ConvPoint_Keras
0.720
ConvPoint: Continuous Convolutions for Point Cloud Processing
FKAConv
0.827
FKAConv: Feature-Kernel Alignment for Point Cloud Convolution
DA-supervised
0.638
CLOUDSPAM: Contrastive Learning On Unlabeled Data for Segmentation and Pre-Training Using Aggregated Point Clouds and MoCo
KPConv deform
0.759
KPConv: Flexible and Deformable Convolution for Point Clouds
CLOUDSPAM
0.738
CLOUDSPAM: Contrastive Learning On Unlabeled Data for Segmentation and Pre-Training Using Aggregated Point Clouds and MoCo
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