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 51–100 of 272 papers

TitleStatusHype
Serialized Point Mamba: A Serialized Point Cloud Mamba Segmentation Model—0
Dual-level Adaptive Self-Labeling for Novel Class Discovery in Point Cloud SegmentationCode1
Uplifting Range-View-based 3D Semantic Segmentation in Real-Time with Multi-Sensor Fusion—0
fVDB: A Deep-Learning Framework for Sparse, Large-Scale, and High-Performance Spatial IntelligenceCode4
Pamba: Enhancing Global Interaction in Point Clouds via State Space Model—0
ARCH2S: Dataset, Benchmark and Challenges for Learning Exterior Architectural Structures from Point CloudsCode1
Twin Deformable Point Convolutions for Point Cloud Semantic Segmentation in Remote Sensing Scenes—0
3D Annotation-Free Learning by Distilling 2D Open-Vocabulary Segmentation Models for Autonomous DrivingCode1
Filling Missing Values Matters for Range Image-Based Point Cloud Segmentation—0
Machine Vision-Based Assessment of Fall Color Changes and its Relationship with Leaf Nitrogen Concentration—0
ECLAIR: A High-Fidelity Aerial LiDAR Dataset for Semantic SegmentationCode1
OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views—0
RiEMann: Near Real-Time SE(3)-Equivariant Robot Manipulation without Point Cloud Segmentation—0
CurbNet: Curb Detection Framework Based on LiDAR Point Cloud SegmentationCode1
EffiPerception: an Efficient Framework for Various Perception Tasks—0
Refining Segmentation On-the-Fly: An Interactive Framework for Point Cloud Semantic Segmentation—0
3DRef: 3D Dataset and Benchmark for Reflection Detection in RGB and Lidar Data—0
Region-Transformer: Self-Attention Region Based Class-Agnostic Point Cloud Segmentation—0
Dynamic Prototype Adaptation with Distillation for Few-shot Point Cloud SegmentationCode0
Symbol as Points: Panoptic Symbol Spotting via Point-based RepresentationCode2
MirageRoom: 3D Scene Segmentation with 2D Pre-trained Models by Mirage Projection—0
Construct to Associate: Cooperative Context Learning for Domain Adaptive Point Cloud Segmentation—0
Multi-modality Affinity Inference for Weakly Supervised 3D Semantic SegmentationCode0
PointCT: Point Central Transformer Network for Weakly-supervised Point Cloud Semantic SegmentationCode1
Point Cloud Segmentation Using Transfer Learning with RandLA-Net: A Case Study on Urban Areas—0
T-MAE: Temporal Masked Autoencoders for Point Cloud Representation LearningCode0
Transferring CLIP's Knowledge into Zero-Shot Point Cloud Semantic Segmentation—0
Densify Your Labels: Unsupervised Clustering with Bipartite Matching for Weakly Supervised Point Cloud Segmentation—0
Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More—0
Generalized Robot 3D Vision-Language Model with Fast Rendering and Pre-Training Vision-Language AlignmentCode3
OneFormer3D: One Transformer for Unified Point Cloud SegmentationCode2
DatasetNeRF: Efficient 3D-aware Data Factory with Generative Radiance FieldsCode0
U3DS^3: Unsupervised 3D Semantic Scene Segmentation—0
Leveraging Large-Scale Pretrained Vision Foundation Models for Label-Efficient 3D Point Cloud Segmentation—0
2D-3D Interlaced Transformer for Point Cloud Segmentation with Scene-Level Supervision—0
PointHR: Exploring High-Resolution Architectures for 3D Point Cloud SegmentationCode1
Addressing Data Misalignment in Image-LiDAR Fusion on Point Cloud Segmentation—0
Generalized Few-Shot Point Cloud Segmentation Via Geometric WordsCode1
Towards Robust Few-shot Point Cloud Semantic SegmentationCode0
Compositional Semantic Mix for Domain Adaptation in Point Cloud SegmentationCode1
Hierarchical Point-based Active Learning for Semi-supervised Point Cloud Semantic SegmentationCode1
Autonomous Point Cloud Segmentation for Power Lines Inspection in Smart Grid—0
Boosting Few-shot 3D Point Cloud Segmentation via Query-Guided EnhancementCode1
pCTFusion: Point Convolution-Transformer Fusion with Semantic Aware Loss for Outdoor LiDAR Point Cloud SegmentationCode0
Clustering based Point Cloud Representation Learning for 3D AnalysisCode1
See More and Know More: Zero-shot Point Cloud Segmentation via Multi-modal Visual Data—0
Achelous: A Fast Unified Water-surface Panoptic Perception Framework based on Fusion of Monocular Camera and 4D mmWave RadarCode1
BPNet: Bézier Primitive Segmentation on 3D Point CloudsCode1
Point2Point : A Framework for Efficient Deep Learning on Hilbert sorted Point Clouds with applications in Spatio-Temporal Occupancy Prediction—0
Dynamic Clustering Transformer Network for Point Cloud Segmentation—0
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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