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 81–90 of 272 papers

Title	Date	Tasks	Status	Score
PFSD: A Multi-Modal Pedestrian-Focus Scene Dataset for Rich Tasks in Semi-Structured Environments	Feb 21, 2025	AttributeAutonomous Driving	CodeCode Available	5
Automatic Tooth Segmentation from 3D Dental Model using Deep Learning: A Quantitative Analysis of what can be learnt from a Single 3D Dental Model	Sep 16, 2022	Data AugmentationPoint Cloud Segmentation	CodeCode Available	5
Oriented Point Sampling for Plane Detection in Unorganized Point Clouds	May 4, 2019	Point Cloud Segmentation	CodeCode Available	5
A Dataset for Analysing Complex Document Layouts in the Digital Humanities and Its Evaluation with Krippendorff’s Alpha	Sep 20, 2022	Instance SegmentationObject Detection	CodeCode Available	5
DatasetNeRF: Efficient 3D-aware Data Factory with Generative Radiance Fields	Nov 18, 2023	DecoderPoint Cloud Segmentation	CodeCode Available	5
On Universal Equivariant Set Networks	Oct 6, 2019	Point Cloud Segmentation	CodeCode Available	5
A Unified Point-Based Framework for 3D Segmentation	Aug 1, 2019	Point Cloud SegmentationSegmentation	CodeCode Available	5
On Adversarial Robustness of Point Cloud Semantic Segmentation	Dec 11, 2021	Adversarial RobustnessAutonomous Driving	CodeCode Available	5
On the Over-Smoothing Problem of CNN Based Disparity Estimation	Oct 1, 2019	Disparity EstimationPoint Cloud Segmentation	CodeCode Available	5
pCTFusion: Point Convolution-Transformer Fusion with Semantic Aware Loss for Outdoor LiDAR Point Cloud Segmentation	Jul 27, 2023	Point Cloud SegmentationSegmentation	CodeCode Available	5

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	OcCo-PCN	mean Corruption Error (mCE)	1.17	—	Unverified
2	OcCo-PointNet	mean Corruption Error (mCE)	1.13	—	Unverified
3	PointNet++	mean Corruption Error (mCE)	1.11	—	Unverified
4	PointTransformers	mean Corruption Error (mCE)	1.05	—	Unverified
5	PointMLP	mean Corruption Error (mCE)	0.98	—	Unverified
6	PointMAE	mean Corruption Error (mCE)	0.93	—	Unverified
7	GDANet	mean Corruption Error (mCE)	0.92	—	Unverified
8	GDANet	mean Corruption Error (mCE)	0.89	—	Unverified