3D Point Cloud Registration with Multi-Scale Architecture and Unsupervised Transfer Learning

@article{Horache20213DPC,
  title={3D Point Cloud Registration with Multi-Scale Architecture and Unsupervised Transfer Learning},
  author={Sofiane Horache and Jean-Emmanuel Deschaud and Franccois Goulette},
  journal={2021 International Conference on 3D Vision (3DV)},
  year={2021},
  pages={1351-1361}
}
We propose a method for generalizing deep learning for 3D point cloud registration on new, totally different datasets. It is based on two components, MS-SVConv and UDGE. Using Multi-Scale Sparse Voxel Convolution, MSSVConv is a fast deep neural network that outputs the descriptors from point clouds for 3D registration between two scenes. UDGE is an algorithm for transferring deep networks on unknown datasets in a unsupervised way. The interest of the proposed method appears while using the two… 
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