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 1–50 of 272 papers

TitleStatusHype
TSDASeg: A Two-Stage Model with Direct Alignment for Interactive Point Cloud Segmentation—0
Enhancing Human-Robot Collaboration: A Sim2Real Domain Adaptation Algorithm for Point Cloud Segmentation in Industrial Environments—0
Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting—0
OpenMaskDINO3D : Reasoning 3D Segmentation via Large Language ModelCode1
APCoTTA: Continual Test-Time Adaptation for Semantic Segmentation of Airborne LiDAR Point CloudsCode0
WLTCL: Wide Field-of-View 3-D LiDAR Truck Compartment Automatic Localization System—0
3D-PointZshotS: Geometry-Aware 3D Point Cloud Zero-Shot Semantic Segmentation Narrowing the Visual-Semantic GapCode0
ProtoGuard-guided PROPEL: Class-Aware Prototype Enhancement and Progressive Labeling for Incremental 3D Point Cloud Segmentation—0
Robust Unsupervised Domain Adaptation for 3D Point Cloud Segmentation Under Source Adversarial Attacks—0
DINO in the Room: Leveraging 2D Foundation Models for 3D SegmentationCode2
GeoT: Geometry-guided Instance-dependent Transition Matrix for Semi-supervised Tooth Point Cloud SegmentationCode0
Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language ModelCode2
Depth-Aware Range Image-Based Model for Point Cloud Segmentation—0
Deep Unsupervised Segmentation of Log Point Clouds—0
Joint 3D Point Cloud Segmentation using Real-Sim Loop: From Panels to Trees and Branches—0
Label-Efficient LiDAR Semantic Segmentation with 2D-3D Vision Transformer Adapters—0
Explainable LiDAR 3D Point Cloud Segmentation and Clustering for Detecting Airplane-Generated Wind Turbulence—0
PFSD: A Multi-Modal Pedestrian-Focus Scene Dataset for Rich Tasks in Semi-Structured EnvironmentsCode0
An Experimental Study of SOTA LiDAR Segmentation Models—0
Ground Awareness in Deep Learning for Large Outdoor Point Cloud Segmentation—0
3DSES: an indoor Lidar point cloud segmentation dataset with real and pseudo-labels from a 3D model—0
LiDAR-Based Vehicle Detection and Tracking for Autonomous Racing—0
The 2nd Place Solution from the 3D Semantic Segmentation Track in the 2024 Waymo Open Dataset Challenge—0
MRG: A Multi-Robot Manufacturing Digital Scene Generation Method Using Multi-Instance Point Cloud Registration—0
Hyperbolic Uncertainty-Aware Few-Shot Incremental Point Cloud Segmentation—0
Generative Hard Example Augmentation for Semantic Point Cloud Segmentation—0
CamPoint: Boosting Point Cloud Segmentation with Virtual Camera—0
Impact of color and mixing proportion of synthetic point clouds on semantic segmentationCode0
The Bare Necessities: Designing Simple, Effective Open-Vocabulary Scene Graphs—0
Textured As-Is BIM via GIS-informed Point Cloud Segmentation—0
Towards Cross-device and Training-free Robotic Grasping in 3D Open World—0
BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation—0
Biomass phenotyping of oilseed rape through UAV multi-view oblique imaging with 3DGS and SAM model—0
Multiscale Graph Construction Using Non-local Cluster Features—0
Automated Image-Based Identification and Consistent Classification of Fire Patterns with Quantitative Shape Analysis and Spatial Location Identification—0
Multimodality Helps Few-Shot 3D Point Cloud Semantic SegmentationCode2
Exploring contextual modeling with linear complexity for point cloud segmentation—0
Generalizable Humanoid Manipulation with 3D Diffusion PoliciesCode4
Evaluating the Impact of Point Cloud Colorization on Semantic Segmentation Accuracy—0
Underground Mapping and Localization Based on Ground-Penetrating Radar—0
Lidar Panoptic Segmentation in an Open WorldCode1
Efficiently Expanding Receptive Fields: Local Split Attention and Parallel Aggregation for Enhanced Large-scale Point Cloud Semantic Segmentation—0
When 3D Partial Points Meets SAM: Tooth Point Cloud Segmentation with Sparse LabelsCode0
Towards Modality-agnostic Label-efficient Segmentation with Entropy-Regularized Distribution AlignmentCode1
GSTran: Joint Geometric and Semantic Coherence for Point Cloud SegmentationCode0
Trainable Pointwise Decoder Module for Point Cloud Segmentation—0
Fine-grained Metrics for Point Cloud Semantic Segmentation—0
Scale Disparity of Instances in Interactive Point Cloud Segmentation—0
SegPoint: Segment Any Point Cloud via Large Language Model—0
Dual-level Adaptive Self-Labeling for Novel Class Discovery in Point Cloud SegmentationCode1
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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