Cascading Feature Extraction for Fast Point Cloud Registration
This repository contains the source code for the paper [Arxive link comming soon].
Method | rotation error (˚) | translation error (cm) | chamfer error | inferrence time (ms) |
---|---|---|---|---|
FGR | 31.4 | 20 | 0.012 | 34 |
DCP-V2 | 12.6 | 17 | 0.011 | 12 |
RPMNet (Optim) | 1.71 | 1.8 | 0.00085 | 58 |
RGM | 1.56 | 1.5 | 0.00084 | 174 |
Proposed | 1.23 | 1.3 | 0.00076 | 17 |
Getting Started
cascading_feature_extraction
|- datasets/
|- modelnet40_ply_hdf5_2048.zip
|- modelnet40_ply_hdf5_2048/
|- src/
...
|- pretrained/
|- modelnet40.pth
Download dataset
Please add --insecure
at the end of the installation command, in order of lack of certificate
curl -O https://shapenet.cs.stanford.edu/media/modelnet40_ply_hdf5_2048.zip
Requirements
pip install -r requirements
We confirmed that the code runs at Python>=3.7
.
Train
cd src
python train.py
Test
cd src
python eval.py --resume ../pretrained/modelnet40.pth
Citation
@inproceedings{hisadome2021,
title = {Cascading Feature Extraction for Fast Point Cloud Registration},
author = {Hisadome, Yoichiro and Matsui, Yusuke},
booktitle = {Proceedings of the British Machine Vision Conference},
year={2021}
}
Acknowledgements
Our code is mainly based on RPMNet. We appriciate them for making the code available.