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

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Showing 51–100 of 272 papers

TitleStatusHype
ECLAIR: A High-Fidelity Aerial LiDAR Dataset for Semantic SegmentationCode1
Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor SceneCode1
Learning with Noisy Labels for Robust Point Cloud SegmentationCode1
Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene CompletionCode1
GndNet: Fast Ground Plane Estimation and Point Cloud Segmentation for Autonomous VehiclesCode1
Position-Guided Point Cloud Panoptic Segmentation TransformerCode1
Reliability-Adaptive Consistency Regularization for Weakly-Supervised Point Cloud SegmentationCode1
Dense-Resolution Network for Point Cloud Classification and SegmentationCode1
Spatiotemporal Self-supervised Learning for Point Clouds in the WildCode1
GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR SegmentationCode1
Robust Point Cloud Segmentation with Noisy AnnotationsCode1
Differentiable Graph Module (DGM) for Graph Convolutional NetworksCode1
AGCN: Adversarial Graph Convolutional Network for 3D Point Cloud SegmentationCode1
HGL: Hierarchical Geometry Learning for Test-time Adaptation in 3D Point Cloud SegmentationCode1
DLA-Net: Learning Dual Local Attention Features for Semantic Segmentation of Large-Scale Building Facade Point CloudsCode1
Boosting Few-shot 3D Point Cloud Segmentation via Query-Guided EnhancementCode1
BPNet: Bézier Primitive Segmentation on 3D Point CloudsCode1
Dual-level Adaptive Self-Labeling for Novel Class Discovery in Point Cloud SegmentationCode1
SemAffiNet: Semantic-Affine Transformation for Point Cloud SegmentationCode1
Dynamic Graph CNN for Learning on Point CloudsCode1
Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point ModelingCode1
SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud SegmentationCode1
Can We Solve 3D Vision Tasks Starting from A 2D Vision Transformer?Code1
Hierarchical Point-based Active Learning for Semi-supervised Point Cloud Semantic SegmentationCode1
Diffusion Unit: Interpretable Edge Enhancement and Suppression Learning for 3D Point Cloud SegmentationCode1
Knowledge Distillation from 3D to Bird's-Eye-View for LiDAR Semantic SegmentationCode1
Weakly Supervised Semantic Point Cloud Segmentation:Towards 10X Fewer LabelsCode1
PriFit: Learning to Fit Primitives Improves Few Shot Point Cloud SegmentationCode1
Scalable Certified Segmentation via Randomized SmoothingCode0
RGCNN: Regularized Graph CNN for Point Cloud SegmentationCode0
Rethinking 3D LiDAR Point Cloud SegmentationCode0
Projection-based Point Convolution for Efficient Point Cloud SegmentationCode0
Segmentation of EM showers for neutrino experiments with deep graph neural networksCode0
PointSIFT: A SIFT-like Network Module for 3D Point Cloud Semantic SegmentationCode0
Automatic Tooth Segmentation from 3D Dental Model using Deep Learning: A Quantitative Analysis of what can be learnt from a Single 3D Dental ModelCode0
A Dataset for Analysing Complex Document Layouts in the Digital Humanities and Its Evaluation with Krippendorff’s AlphaCode0
DatasetNeRF: Efficient 3D-aware Data Factory with Generative Radiance FieldsCode0
A Unified Point-Based Framework for 3D SegmentationCode0
On Adversarial Robustness of Point Cloud Semantic SegmentationCode0
PointWeb: Enhancing Local Neighborhood Features for Point Cloud ProcessingCode0
Oriented Point Sampling for Plane Detection in Unorganized Point CloudsCode0
On the Over-Smoothing Problem of CNN Based Disparity EstimationCode0
On Universal Equivariant Set NetworksCode0
pCTFusion: Point Convolution-Transformer Fusion with Semantic Aware Loss for Outdoor LiDAR Point Cloud SegmentationCode0
APCoTTA: Continual Test-Time Adaptation for Semantic Segmentation of Airborne LiDAR Point CloudsCode0
Fast 3D Line Segment Detection From Unorganized Point CloudCode0
Multi-modality Affinity Inference for Weakly Supervised 3D Semantic SegmentationCode0
MmWave Radar Point Cloud Segmentation using GMM in Multimodal Traffic MonitoringCode0
Monte Carlo Convolution for Learning on Non-Uniformly Sampled Point CloudsCode0
PFSD: A Multi-Modal Pedestrian-Focus Scene Dataset for Rich Tasks in Semi-Structured EnvironmentsCode0
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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