Deep Global Registration
Chris Choy*, Wei Dong*, Vladlen Koltun
CVPR 2020 (Oral)
Abstract
We present Deep Global Registration, a differentiable framework for pairwise registration of real-world 3D scans.
Deep global registration is based on three modules:
- a 6-dimensional convolutional network for correspondence confidence prediction,
- a differentiable Weighted Procrustes algorithm for closed-form pose estimation,
- and a robust gradient-based SE(3) optimizer for pose refinement.
Experiments demonstrate that our approach outperforms state-of-the-art methods, both learning-based and classical, on real-world data.
Citation
@inproceedings{choy2020deep,
title={Deep Global Registration},
author={Choy, Christopher and Dong, Wei and Koltun, Vladlen},
booktitle={CVPR},
year={2020}
}