3D Instance Segmentation

59 papers with code • 8 benchmarks • 13 datasets

Image: OccuSeg

Libraries

Use these libraries to find 3D Instance Segmentation models and implementations

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

wolny/pytorch-3dunet 21 Jun 2016

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

meidachen/STPLS3D 17 Mar 2022

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

WXinlong/ASIS CVPR 2019

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

hlei-ziyan/SPH3D-GCN 20 Sep 2019

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 20 Dec 2019

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.