README.md

Unsupervised Point Cloud Registration via Salient Points Analysis (SPA)

Salient Points Analysis (SPA) is an unsupervised learning based method for registration of 3D point cloud objcets. This is an official implementation of SPA by Pranav Kadam, Min Zhang, Shan Liu and C.-C. Jay Kuo. This work was carried out at Media Communications Lab (MCL), University of Southern California, USA.

Introduction

In this work, we propose Salient Points Analysis (SPA), a method for registering 3D point clouds. The SPA paper can be found here.

Citation

If you find our work useful in your research, please consider citing:

@inproceedings{kadam2020unsupervised,
  title={Unsupervised Point Cloud Registration via Salient Points Analysis (SPA)},
  author={Kadam, Pranav and Zhang, Min and Liu, Shan and Kuo, C-C Jay},
  booktitle={2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)},
  pages={5--8},
  year={2020},
  organization={IEEE}
}