CorrI2P

CorrI2P: Deep Image-to-Point Cloud Registration via Dense Correspondence

arxiv TCSVT
Accepted by IEEE TCSVT

Data

KITTI

Here we provide KITTI prepared.
You can download it here.
Unzip these files, and the directory is as follows:

kitti
-calib
--00
--01
...
-sequences
--00
--01
...

NuScenes

Here we provide nuScenes prepared.
You can download it here.
We also provide the script for preparing NuScenes dataset in nuScenes_script folder (reffer to DeepI2P). They can be used to generate nuscenes dataset.

Usage

Install required lib as SO-Net or DeepI2P.

Train

python train.py

Test

python eval_all.py
python cal_error_all.py
python analysis.py

Note: There would be lots of intermediate results, please leave enough storage space.

Citation

@ARTICLE{CORRI2P,
  author={Ren, Siyu and Zeng, Yiming and Hou, Junhui and Chen, Xiaodong},
  journal={IEEE Transactions on Circuits and Systems for Video Technology}, 
  title={CorrI2P: Deep Image-to-Point Cloud Registration via Dense Correspondence}, 
  year={2022},
  volume={},
  number={},
  pages={1-1},
  doi={10.1109/TCSVT.2022.3208859}}

Acknowledgement

We thank the authors of DeepI2P for their public code.

If you want to use our code, please cite our work.