Learning Gaussian Instance Segmentation in Point Clouds

07/20/2020
by   Shih-Hung Liu, et al.
0

This paper presents a novel method for instance segmentation of 3D point clouds. The proposed method is called Gaussian Instance Center Network (GICN), which can approximate the distributions of instance centers scattered in the whole scene as Gaussian center heatmaps. Based on the predicted heatmaps, a small number of center candidates can be easily selected for the subsequent predictions with efficiency, including i) predicting the instance size of each center to decide a range for extracting features, ii) generating bounding boxes for centers, and iii) producing the final instance masks. GICN is a single-stage, anchor-free, and end-to-end architecture that is easy to train and efficient to perform inference. Benefited from the center-dictated mechanism with adaptive instance size selection, our method achieves state-of-the-art performance in the task of 3D instance segmentation on ScanNet and S3DIS datasets.

READ FULL TEXT

page 3

page 5

page 12

page 13

page 14

page 16

page 17

page 18

research
06/04/2019

Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds

We propose a novel, conceptually simple and general framework for instan...
research
09/27/2019

Rethinking Task and Metrics of Instance Segmentation on 3D Point Clouds

Instance segmentation on 3D point clouds is one of the most extensively ...
research
07/07/2021

Learning Stixel-based Instance Segmentation

Stixels have been successfully applied to a wide range of vision tasks i...
research
11/30/2018

TextMountain: Accurate Scene Text Detection via Instance Segmentation

In this paper, we propose a novel scene text detection method named Text...
research
08/17/2022

Look in Different Views: Multi-Scheme Regression Guided Cell Instance Segmentation

Cell instance segmentation is a new and challenging task aiming at joint...
research
07/20/2022

NeuralBF: Neural Bilateral Filtering for Top-down Instance Segmentation on Point Clouds

We introduce a method for instance proposal generation for 3D point clou...
research
03/14/2020

OccuSeg: Occupancy-aware 3D Instance Segmentation

3D instance segmentation, with a variety of applications in robotics and...

Please sign up or login with your details

Forgot password? Click here to reset