Official repo for CoRL 2021 paper Correspondence-Free Point Cloud Registration with SO(3)-Equivariant Implicit Shape Representations (link)
This repo has the same environment as the occupancy network repo. The code is also developed based on that repo.
The preprocessed ModelNet40 dataset can be downloaded at this Google Drive link. It is processed by this repo to obtain water-tight meshes and occupancy value for points in the space, which are not available in the original ModelNet40 dataset (mentioned in the OccNet repo). Extract the files and create a symbolic link named ModelNet40_install under the root of this repo.
Examples are given in the files run_train.sh and run_test.sh.
If this work is helpful for your research, please consider citing our work:
@inproceedings{zhu2022correspondence,
title={Correspondence-free point cloud registration with SO (3)-equivariant implicit shape representations},
author={Zhu, Minghan and Ghaffari, Maani and Peng, Huei},
booktitle={Conference on Robot Learning},
pages={1412--1422},
year={2022},
organization={PMLR}
}