3D Instance Segmentation
59 papers with code • 8 benchmarks • 13 datasets
Image: OccuSeg
Benchmarks
These leaderboards are used to track progress in 3D Instance Segmentation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
Libraries
Use these libraries to find 3D Instance Segmentation models and implementations
ScanNet
S3DIS
KITTI-360
PartNet
SceneNN
STPLS3D
ScanNet200
CREMI
FOR-instance
Most implemented papers
Mask R-CNN
tensorflow/models
•
•
ICCV 2017
Our approach efficiently detects objects in an image while simultaneously generating a high-quality segmentation mask for each instance.
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
This paper introduces a network for volumetric segmentation that learns from sparsely annotated volumetric images.
PointCNN: Convolution On $\mathcal{X}$-Transformed Points
yangyanli/PointCNN
•
•
NeurIPS 2018
The proposed method is a generalization of typical CNNs to feature learning from point clouds, thus we call it PointCNN.
PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understanding
yangyanli/PointCNN
•
•
CVPR 2019
We present PartNet: a consistent, large-scale dataset of 3D objects annotated with fine-grained, instance-level, and hierarchical 3D part information.
STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset
Specifically, we introduce a synthetic aerial photogrammetry point clouds generation pipeline that takes full advantage of open geospatial data sources and off-the-shelf commercial packages.
Associatively Segmenting Instances and Semantics in Point Clouds
A 3D point cloud describes the real scene precisely and intuitively. To date how to segment diversified elements in such an informative 3D scene is rarely discussed.
Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds
We propose a spherical kernel for efficient graph convolution of 3D point clouds.
JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds
dlinzhao/JSNet
•
•
In this paper, we propose a novel joint instance and semantic segmentation approach, which is called JSNet, in order to address the instance and semantic segmentation of 3D point clouds simultaneously.
PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
Pointcept/Pointcept
•
•
CVPR 2020
Instance segmentation is an important task for scene understanding.
ISBNet: a 3D Point Cloud Instance Segmentation Network with Instance-aware Sampling and Box-aware Dynamic Convolution
VinAIResearch/ISBNet
•
•
CVPR 2023
Existing 3D instance segmentation methods are predominated by the bottom-up design -- manually fine-tuned algorithm to group points into clusters followed by a refinement network.
