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
Generative Hard Example Augmentation for Semantic Point Cloud Segmentation—0
Hyperbolic Uncertainty-Aware Few-Shot Incremental Point Cloud Segmentation—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
Multiscale Graph Construction Using Non-local Cluster Features—0
Biomass phenotyping of oilseed rape through UAV multi-view oblique imaging with 3DGS and SAM model—0
Automated Image-Based Identification and Consistent Classification of Fire Patterns with Quantitative Shape Analysis and Spatial Location Identification—0
Exploring contextual modeling with linear complexity for point cloud segmentation—0
Evaluating the Impact of Point Cloud Colorization on Semantic Segmentation Accuracy—0
Underground Mapping and Localization Based on Ground-Penetrating Radar—0
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
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
Serialized Point Mamba: A Serialized Point Cloud Mamba Segmentation Model—0
Uplifting Range-View-based 3D Semantic Segmentation in Real-Time with Multi-Sensor Fusion—0
Pamba: Enhancing Global Interaction in Point Clouds via State Space Model—0
Twin Deformable Point Convolutions for Point Cloud Semantic Segmentation in Remote Sensing Scenes—0
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
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
EffiPerception: an Efficient Framework for Various Perception Tasks—0
3DRef: 3D Dataset and Benchmark for Reflection Detection in RGB and Lidar Data—0
Refining Segmentation On-the-Fly: An Interactive Framework for Point Cloud Semantic Segmentation—0
Region-Transformer: Self-Attention Region Based Class-Agnostic Point Cloud Segmentation—0
Dynamic Prototype Adaptation with Distillation for Few-shot Point Cloud SegmentationCode0
Construct to Associate: Cooperative Context Learning for Domain Adaptive Point Cloud Segmentation—0
MirageRoom: 3D Scene Segmentation with 2D Pre-trained Models by Mirage Projection—0
Multi-modality Affinity Inference for Weakly Supervised 3D Semantic SegmentationCode0
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
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
Addressing Data Misalignment in Image-LiDAR Fusion on Point Cloud Segmentation—0
Towards Robust Few-shot Point Cloud Semantic SegmentationCode0
Autonomous Point Cloud Segmentation for Power Lines Inspection in Smart Grid—0
pCTFusion: Point Convolution-Transformer Fusion with Semantic Aware Loss for Outdoor LiDAR Point Cloud SegmentationCode0
See More and Know More: Zero-shot Point Cloud Segmentation via Multi-modal Visual Data—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