3D Instance Segmentation

27 papers with code • 6 benchmarks • 10 datasets

Image: OccuSeg

Libraries

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

Most implemented papers

Mask R-CNN

matterport/Mask_RCNN 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.

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.

STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset

hustvl/HAIS 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.

SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation

laughtervv/SGPN CVPR 2018

Experimental results on various 3D scenes show the effectiveness of our method on 3D instance segmentation, and we also evaluate the capability of SGPN to improve 3D object detection and semantic segmentation results.

GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud

ericyi/GSPN CVPR 2019

We introduce a novel 3D object proposal approach named Generative Shape Proposal Network (GSPN) for instance segmentation in point cloud data.