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

Showing 201–250 of 272 papers

TitleStatusHype
Scalable Certified Segmentation via Randomized SmoothingCode0
Self-Supervised Learning on 3D Point Clouds by Learning Discrete Generative Models—0
Semantically Adversarial Scenario Generation with Explicit Knowledge Guidance—0
Revisiting 2D Convolutional Neural Networks for Graph-based Applications—0
Weakly Supervised Pseudo-Label assisted Learning for ALS Point Cloud Semantic Segmentation—0
Cross-Level Cross-Scale Cross-Attention Network for Point Cloud Representation—0
Segmentation of EM showers for neutrino experiments with deep graph neural networksCode0
RPVNet: A Deep and Efficient Range-Point-Voxel Fusion Network for LiDAR Point Cloud Segmentation—0
Deep Learning Based 3D Segmentation: A Survey—0
From a Point Cloud to a Simulation Model: Bayesian Segmentation and Entropy based Uncertainty Estimation for 3D Modelling—0
PIG-Net: Inception based Deep Learning Architecture for 3D Point Cloud Segmentation—0
Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach—0
Deep Parametric Continuous Convolutional Neural Networks—0
Boundary-Aware Geometric Encoding for Semantic Segmentation of Point CloudsCode0
TempNet: Online Semantic Segmentation on Large-Scale Point Cloud Series—0
Compositional Prototype Network with Multi-view Comparision for Few-Shot Point Cloud Semantic Segmentation—0
Uncertainty Estimation in Deep Neural Networks for Point Cloud Segmentation in Factory Planning—0
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
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
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
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
SegGCN: Efficient 3D Point Cloud Segmentation With Fuzzy Spherical Kernel—0
Few-Shot Learning of Part-Specific Probability Space for 3D Shape Segmentation—0
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
YOLO and K-Means Based 3D Object Detection Method on Image and Point Cloud—0
3D Object Detection Method Based on YOLO and K-Means for Image and Point Clouds—0
Indoor Point Cloud Segmentation Using Iterative Gaussian Mapping and Improved Model Fitting—0
Local Model Feature Transformations—0
Photogrammetric point cloud segmentation and object information extraction for creating virtual environments and simulations—0
Point Cloud Segmentation based on Hypergraph Spectral Clustering—0
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
Show:102550
← PrevPage 5 of 6Next →

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