Classification of Point Cloud Scenes with Multiscale Voxel Deep Network
2018-04-10Code Available0· sign in to hype
Xavier Roynard, Jean-Emmanuel Deschaud, François Goulette
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ReproduceCode
- github.com/xroynard/ms_deepvoxscenepytorch★ 0
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).
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| Semantic3D | MSDeepVoxNet | mIoU | 65.3 | — | Unverified |