English

Classification of Point Cloud Scenes with Multiscale Voxel Deep Network

Computer Vision and Pattern Recognition 2018-04-11 v1

Abstract

In this article we describe a new convolutional neural network (CNN) to classify 3D point clouds of urban or indoor scenes. Solutions are given to the problems encountered working on scene point clouds, and a network is described that allows for point classification using only the position of points in a multi-scale neighborhood. On the reduced-8 Semantic3D benchmark [Hackel et al., 2017], this network, ranked second, beats the state of the art of point classification methods (those not using a regularization step).

Keywords

Cite

@article{arxiv.1804.03583,
  title  = {Classification of Point Cloud Scenes with Multiscale Voxel Deep Network},
  author = {Xavier Roynard and Jean-Emmanuel Deschaud and François Goulette},
  journal= {arXiv preprint arXiv:1804.03583},
  year   = {2018}
}

Comments

preprint

R2 v1 2026-06-23T01:19:29.239Z