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PCRNet: Point Cloud Registration Network using PointNet Encoding

Source Code Author: Vinit Sarode and Xueqian Li

Paper | Website | Video | Pytorch Implementation

<p align="center"> <img src="https://github.com/vinits5/pcrnet/blob/master/images/first_fig.png" height="300"> </p>

Requirements:

  1. Cuda 10
  2. tensorflow==1.14
  3. transforms3d==0.3.1
  4. h5py==2.9.0

Dataset:

Path for dataset: Link

  1. Download 'train_data' folder from above link for iterative PCRNet.
  2. Download 'car_data' folder from above link for PCRNet.

Pretrained Model:

Download pretrained models from Link

How to use code:

Compile loss functions:

  1. cd utils/pc_distance
  2. make -f makefile_10.0 clean
  3. make -f makefile_10.0

Train Iterative-PCRNet:

  1. chmod +x train_itrPCRNet.sh
  2. ./train_itrPCRNet.sh

Train PCRNet:

  1. chmod +x train_PCRNet.sh
  2. ./train_PCRNet.sh

Citation

@InProceedings{vsarode2019pcrnet,
       author = {Sarode, Vinit and Li, Xueqian and Goforth, Hunter and Aoki, Yasuhiro and Arun Srivatsan, Rangaprasad and Lucey, Simon and Choset, Howie},
       title = {PCRNet: Point Cloud Registration Network using PointNet Encoding},
       month = {Aug},
       year = {2019}
}