This work is based on our SIGGRAPH Asia 2018 paper. You can find the arXiv version of the paper here. In this repository, we release the training and evaluation code, data as well as the pre-trained models.
Download training and validation data from
https://shapenet.cs.stanford.edu/ericyi/data_partmob.zip
Compile the PointNet++ code in "pointnet2"
Train the corrspondence proposal and the flow module through
python train.py --stage 1
Train the hypothesis generation and the verification submodule through
python train.py --stage 2
Train the hypothesis selection submodule through
python train.py --stage 3
Evaluate the model through
python evaluation.py
You can also download the pretrained model from the following link:
https://shapenet.cs.stanford.edu/ericyi/pretrained_model_partmob.zip
Our code and data are released under MIT License (see LICENSE file for details).