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DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction (3DV 2021)

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This repo is the implementation of DPC. Created by Itai Lang*, Dvir Ginzburg*, Shai Avidan, and Dan Raviv from Tel Aviv University. <br> *Equal contribution

PWC

<img src=./data/images/humans.gif width="410" /><img src=./data/images/cats.gif width="550" />  

Architecture   Cross Similarity

Tested environment

Lower CUDA and PyTorch versions should work as well.

 

Contents

 

Installation

Please follow installation.sh or simply run

bash installation.sh 

 

Datasets

The method was evaluated on:

 

Training

For training run

python train_point_corr.py --dataset_name <surreal/tosca/shrec/smal>

The code is based on PyTorch-Lightning, all PL hyperparameters are supported. (limit_train/val/test_batches, check_val_every_n_epoch etc.)

 

Tensorboard support

All metrics are being logged automatically and stored in

output/shape_corr/DeepPointCorr/arch_DeepPointCorr/dataset_name_<name>/run_<num>

Run tesnroboard --logdir=<path> to see the the logs.

Example of tensorboard output:

tensorboard

 

Inference

For testing, simply add --do_train false flag, followed by --resume_from_checkpoint with the relevant checkpoint.

python train_point_corr.py --do_train false  --resume_from_checkpoint <path>

Test phase visualizes each sample, for faster inference pass --show_vis false.

We provide a trained checkpoint repreducing the results provided in the paper, to test and visualize the model run

python train_point_corr.py --show_vis --do_train false --resume_from_checkpoint data/ckpts/surreal_ckpt.ckpt

Results  

Citing & Authors

If you find this repository helpful feel free to cite our publication -

@InProceedings{lang2021dpc,
  author = {Lang, Itai and Ginzburg, Dvir and Avidan, Shai and Raviv, Dan},
  title = {{DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction}},
  booktitle = {Proceedings of the International Conference on 3D Vision (3DV)},
  pages = {1442--1451},
  year = {2021}
}

Contact: Dvir Ginzburg, Itai Lang.