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 251–272 of 272 papers

TitleStatusHype
T-MAE: Temporal Masked Autoencoders for Point Cloud Representation LearningCode0
Toward better boundary preserved supervoxel segmentation for 3D point cloudsCode0
When 3D Partial Points Meets SAM: Tooth Point Cloud Segmentation with Sparse LabelsCode0
On Adversarial Robustness of Point Cloud Semantic SegmentationCode0
LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable TerrainCode0
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D ImagesCode0
Towards Robust Few-shot Point Cloud Semantic SegmentationCode0
RGCNN: Regularized Graph CNN for Point Cloud SegmentationCode0
LatticeNet: Fast Point Cloud Segmentation Using Permutohedral LatticesCode0
Fast 3D Line Segment Detection From Unorganized Point CloudCode0
Impact of color and mixing proportion of synthetic point clouds on semantic segmentationCode0
Dynamic Prototype Adaptation with Distillation for Few-shot Point Cloud SegmentationCode0
SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point CloudCode0
DatasetNeRF: Efficient 3D-aware Data Factory with Generative Radiance FieldsCode0
cilantro: A Lean, Versatile, and Efficient Library for Point Cloud Data ProcessingCode0
Scalable Certified Segmentation via Randomized SmoothingCode0
Zero-shot point cloud segmentation by transferring geometric primitivesCode0
GSTran: Joint Geometric and Semantic Coherence for Point Cloud SegmentationCode0
Boundary-Aware Geometric Encoding for Semantic Segmentation of Point CloudsCode0
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 Unified Point-Based Framework for 3D SegmentationCode0
Segmentation of EM showers for neutrino experiments with deep graph neural networksCode0
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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