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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–250 of 272 papers

TitleStatusHype
Uncertainty Estimation in Deep Neural Networks for Point Cloud Segmentation in Factory Planning—0
Self-Supervised Learning of Lidar Segmentation for Autonomous Indoor NavigationCode1
Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene CompletionCode1
GndNet: Fast Ground Plane Estimation and Point Cloud Segmentation for Autonomous VehiclesCode1
PBP-Net: Point Projection and Back-Projection Network for 3D Point Cloud Segmentation—0
3D photogrammetry point cloud segmentation using a model ensembling framework—0
Stereo Frustums: A Siamese Pipeline for 3D Object Detection—0
UAV LiDAR Point Cloud Segmentation of A Stack Interchange with Deep Neural Networks—0
Unsupervised Point Cloud Pre-Training via Occlusion CompletionCode1
Semantic Segmentation of Surface from Lidar Point Cloud—0
ePointDA: An End-to-End Simulation-to-Real Domain Adaptation Framework for LiDAR Point Cloud Segmentation—0
Generating synthetic photogrammetric data for training deep learning based 3D point cloud segmentation models—0
Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor SceneCode1
Rethinking 3D LiDAR Point Cloud SegmentationCode0
Semantic Context Encoding for Accurate 3D Point Cloud Segmentation—0
Deep FusionNet for Point Cloud Semantic Segmentation—0
Cascaded Non-local Neural Network for Point Cloud Semantic Segmentation—0
KPRNet: Improving projection-based LiDAR semantic segmentationCode1
Cloud Transformers: A Universal Approach To Point Cloud Processing Tasks—0
SASO: Joint 3D Semantic-Instance Segmentation via Multi-scale Semantic Association and Salient Point Clustering Optimization—0
Few-Shot Learning of Part-Specific Probability Space for 3D Shape Segmentation—0
Weakly Supervised Semantic Point Cloud Segmentation: Towards 10x Fewer LabelsCode1
SegGCN: Efficient 3D Point Cloud Segmentation With Fuzzy Spherical Kernel—0
Dense-Resolution Network for Point Cloud Classification and SegmentationCode1
Fast Geometric Surface based Segmentation of Point Cloud from Lidar Data—0
Weakly Supervised Semantic Segmentation in 3D Graph-Structured Point Clouds of Wild Scenes—0
3D Object Detection Method Based on YOLO and K-Means for Image and Point Clouds—0
YOLO and K-Means Based 3D Object Detection Method on Image and Point Cloud—0
Indoor Point Cloud Segmentation Using Iterative Gaussian Mapping and Improved Model Fitting—0
Local Model Feature Transformations—0
Weakly Supervised Semantic Point Cloud Segmentation:Towards 10X Fewer LabelsCode1
SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud SegmentationCode1
Multi-Path Region Mining For Weakly Supervised 3D Semantic Segmentation on Point CloudsCode1
Photogrammetric point cloud segmentation and object information extraction for creating virtual environments and simulations—0
Differentiable Graph Module (DGM) for Graph Convolutional NetworksCode1
Point Cloud Segmentation based on Hypergraph Spectral Clustering—0
Deep Learning for 3D Point Clouds: A SurveyCode1
FuseSeg: LiDAR Point Cloud Segmentation Fusing Multi-Modal Data—0
Deep-learning-based classification and retrieval of components of a process plant from segmented point clouds—0
LatticeNet: Fast Point Cloud Segmentation Using Permutohedral LatticesCode0
GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise TransformationsCode0
MmWave Radar Point Cloud Segmentation using GMM in Multimodal Traffic MonitoringCode0
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D ImagesCode0
POIRot: A rotation invariant omni-directional pointnet—0
On Universal Equivariant Set NetworksCode0
On the Over-Smoothing Problem of CNN Based Disparity EstimationCode0
IPC-Net: 3D point-cloud segmentation using deep inter-point convolutional layers—0
Point Attention Network for Semantic Segmentation of 3D Point Clouds—0
Learning Propagation for Arbitrarily-structured Data—0
Toward better boundary preserved supervoxel segmentation for 3D point cloudsCode0
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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