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 101–150 of 272 papers

TitleStatusHype
Tinto: Multisensor Benchmark for 3D Hyperspectral Point Cloud Segmentation in the Geosciences—0
OctFormer: Octree-based Transformers for 3D Point CloudsCode2
Urban GeoBIM construction by integrating semantic LiDAR point clouds with as-designed BIM models—0
Knowledge Distillation from 3D to Bird's-Eye-View for LiDAR Semantic SegmentationCode1
Transformer-Based Visual Segmentation: A SurveyCode2
Spatiotemporal Self-supervised Learning for Point Clouds in the WildCode1
Few-Shot 3D Point Cloud Semantic Segmentation via Stratified Class-Specific Attention Based Transformer Network—0
Position-Guided Point Cloud Panoptic Segmentation TransformerCode1
Label Name is Mantra: Unifying Point Cloud Segmentation across Heterogeneous Datasets—0
GeoSpark: Sparking up Point Cloud Segmentation with Geometry Clue—0
Reliability-Adaptive Consistency Regularization for Weakly-Supervised Point Cloud SegmentationCode1
From CAD models to soft point cloud labels: An automatic annotation pipeline for cheaply supervised 3D semantic segmentation—0
Human Vision Based 3D Point Cloud Semantic Segmentation of Large-Scale Outdoor SceneCode1
Learning from Mistakes: Self-Regularizing Hierarchical Representations in Point Cloud Semantic Segmentation—0
Contrastive Learning for Self-Supervised Pre-Training of Point Cloud Segmentation Networks With Image Data—0
SAT: Size-Aware Transformer for 3D Point Cloud Semantic Segmentation—0
Sim2real Transfer Learning for Point Cloud Segmentation: An Industrial Application Case on Autonomous Disassembly—0
ProtoTransfer: Cross-Modal Prototype Transfer for Point Cloud Segmentation—0
Zero-Shot Point Cloud Segmentation by Semantic-Visual Aware SynthesisCode1
Improving Graph Representation for Point Cloud Segmentation via Attentive Filtering—0
Adversarially Masking Synthetic To Mimic Real: Adaptive Noise Injection for Point Cloud Segmentation Adaptation—0
Robust Point Cloud Segmentation with Noisy AnnotationsCode1
Effective Utilisation of Multiple Open-Source Datasets to Improve Generalisation Performance of Point Cloud Segmentation Models—0
PointResNet: Residual Network for 3D Point Cloud Segmentation and Classification—0
Learning Latent Part-Whole Hierarchies for Point Clouds—0
Hypergraph Convolutional Network based Weakly Supervised Point Cloud Semantic Segmentation with Scene-Level Annotations—0
Zero-shot point cloud segmentation by transferring geometric primitivesCode0
Point Transformer V2: Grouped Vector Attention and Partition-based PoolingCode2
COARSE3D: Class-Prototypes for Contrastive Learning in Weakly-Supervised 3D Point Cloud SegmentationCode1
Effective Early Stopping of Point Cloud Neural Networks—0
A Dataset for Analysing Complex Document Layouts in the Digital Humanities and Its Evaluation with Krippendorff’s AlphaCode0
Diffusion Unit: Interpretable Edge Enhancement and Suppression Learning for 3D Point Cloud SegmentationCode1
Automatic Tooth Segmentation from 3D Dental Model using Deep Learning: A Quantitative Analysis of what can be learnt from a Single 3D Dental ModelCode0
Can We Solve 3D Vision Tasks Starting from A 2D Vision Transformer?Code1
FEC: Fast Euclidean Clustering for Point Cloud SegmentationCode2
GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR SegmentationCode1
CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR SegmentationCode1
Dual Adaptive Transformations for Weakly Supervised Point Cloud Segmentation—0
Learning Spatial and Temporal Variations for 4D Point Cloud Segmentation—0
PST: Plant segmentation transformer for 3D point clouds of rapeseed plants at the podding stage—0
3D-model ShapeNet Core Classification using Meta-Semantic LearningCode0
SemAffiNet: Semantic-Affine Transformation for Point Cloud SegmentationCode1
Weakly Supervised 3D Point Cloud Segmentation via Multi-Prototype Learning—0
Point Cloud Semantic Segmentation using Multi Scale Sparse Convolution Neural Network—0
Sequential Point Clouds: A Survey—0
Stratified Transformer for 3D Point Cloud SegmentationCode2
Masked Autoencoders for Point Cloud Self-supervised LearningCode2
Contrastive Boundary Learning for Point Cloud SegmentationCode1
RIConv++: Effective Rotation Invariant Convolutions for 3D Point Clouds Deep LearningCode1
Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP FrameworkCode2
Show:102550
← PrevPage 3 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