SOTAVerified

Point Cloud Segmentation

3D point cloud segmentation is the process of classifying point clouds into multiple homogeneous regions, the points in the same region will have the same properties. The segmentation is challenging because of high redundancy, uneven sampling density, and lack explicit structure of point cloud data. This problem has many applications in robotics such as intelligent vehicles, autonomous mapping and navigation.

Source: 3D point cloud segmentation: A survey

Papers

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Showing 51–75 of 272 papers

TitleStatusHype
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric SpaceCode1
PointNet: Deep Learning on Point Sets for 3D Classification and SegmentationCode1
Learning with Noisy Labels for Robust Point Cloud SegmentationCode1
Position-Guided Point Cloud Panoptic Segmentation TransformerCode1
Generalized Few-Shot Point Cloud Segmentation Via Geometric WordsCode1
RIConv++: Effective Rotation Invariant Convolutions for 3D Point Clouds Deep LearningCode1
SCF-Net: Learning Spatial Contextual Features for Large-Scale Point Cloud SegmentationCode1
Dense-Resolution Network for Point Cloud Classification and SegmentationCode1
Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene CompletionCode1
Spatiotemporal Self-supervised Learning for Point Clouds in the WildCode1
Dual-level Adaptive Self-Labeling for Novel Class Discovery in Point Cloud SegmentationCode1
Differentiable Graph Module (DGM) for Graph Convolutional NetworksCode1
BPNet: Bézier Primitive Segmentation on 3D Point CloudsCode1
AGCN: Adversarial Graph Convolutional Network for 3D Point Cloud SegmentationCode1
FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud SegmentationCode1
DLA-Net: Learning Dual Local Attention Features for Semantic Segmentation of Large-Scale Building Facade Point CloudsCode1
Boosting Few-shot 3D Point Cloud Segmentation via Query-Guided EnhancementCode1
GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR SegmentationCode1
Lidar Panoptic Segmentation in an Open WorldCode1
Dynamic Graph CNN for Learning on Point CloudsCode1
Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor SceneCode1
ECLAIR: A High-Fidelity Aerial LiDAR Dataset for Semantic SegmentationCode1
Can We Solve 3D Vision Tasks Starting from A 2D Vision Transformer?Code1
HGL: Hierarchical Geometry Learning for Test-time Adaptation in 3D Point Cloud SegmentationCode1
OpenMaskDINO3D : Reasoning 3D Segmentation via Large Language ModelCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OcCo-PCNmean Corruption Error (mCE)1.17—Unverified
2OcCo-PointNetmean Corruption Error (mCE)1.13—Unverified
3PointNet++mean Corruption Error (mCE)1.11—Unverified
4PointTransformersmean Corruption Error (mCE)1.05—Unverified
5PointMLPmean Corruption Error (mCE)0.98—Unverified
6PointMAEmean Corruption Error (mCE)0.93—Unverified
7GDANetmean Corruption Error (mCE)0.92—Unverified
8GDANetmean Corruption Error (mCE)0.89—Unverified