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PyTorch>=1.0:https://pytorch.org

scipy>=1.2

numpy

h5py

tqdm

TensorboardX:https://github.com/lanpa/tensorboardX

python main.py --exp_name=dcp_v1 --model=dcp --emb_nn=dgcnn --pointer=identity --head=svd

python main.py --exp_name=dcp_v2 --model=dcp --emb_nn=dgcnn --pointer=transformer --head=svd

python main.py --exp_name=dcp_v1 --model=dcp --emb_nn=dgcnn --pointer=identity --head=svd --eval

or

python main.py --exp_name=dcp_v1 --model=dcp --emb_nn=dgcnn --pointer=identity --head=svd --eval --model_path=xx/yy

python main.py --exp_name=dcp_v2 --model=dcp --emb_nn=dgcnn --pointer=transformer --head=svd --eval

or

python main.py --exp_name=dcp_v2 --model=dcp --emb_nn=dgcnn --pointer=transformer --head=svd --eval --model_path=xx/yy

where xx/yy is the pretrained model

Please cite this paper if you want to use it in your work,

@InProceedings{Wang_2019_ICCV,  title={Deep Closest Point: Learning Representations for Point Cloud Registration},  author={Wang, Yue and Solomon, Justin M.},  booktitle = {The IEEE International Conference on Computer Vision (ICCV)},  month = {October},  year={2019}}

MIT License