Unsupervised Pointcloud Registration via Differentiable Rendering

unsupervisedRR

Unsupervised Pointcloud Registration via Differentiable Rendering
This repository holds all the code and data for our recent work on unsupervised point cloud registration:

UnsupervisedR&R: Unsupervised Pointcloud Registration via Differentiable Rendering
Mohamed El Banani, Luya Gao, Justin Johnson

If you find this code useful, please consider citing:

@inProceedings{elbanani2021unsupervisedrr,
  title={{UnsupervisedR&R: Unsupervised Pointcloud Registration via Differentiable Rendering}},
  author={El Banani, Mohamed and Gao, Luya and Johnson, Justin},
  booktitle={CVPR},
  year={2021},
}

If you have any questions about the paper or the code, please feel free to email me at
[email protected]

Usage Instructions

Acknowledgments

We would like to thank the reviewers and area chairs for their valuable comments and suggestions.
We also thank Nilesh Kulkarni, Karan Desai, Richard Higgins, and Max Smith for many helpful
discussions and feedback on early drafts of this work.

We would also like to acknowledge the following repositories and users for making great code openly
available for us to use:

@pytorch/pytorch
@facebookresearch/pytorch3d for a great 3D vision
library.
@intel-isl/Open3D for easy to use implementations of
traditional methods and great visualizers.
@chrischoy and
@zgojcic for releasing excellent code that allows
for easy geometric registration.