Dual Convolution Mesh Network (DCM Net)
Please stay tuned; we are currently working hard to get the code out quickly.
All of our dependencies can be installed with conda or pip.
- Python 3.7
- PyTorch 1.1 Cuda 10.0
- TensorboardX (Tensorflow and Tensorboard are unfortunately also needed to install this)
- Our fork of PyTorch Geometric (with its accompanying libraries as torch_scatter, torch_cluster, torch_sparse)
Since we adapted PyTorch Geometric to enable graph level support, you need to install our fork as follows:
cd pytorch_geometric python setup.py install
Please refer to https://github.com/ScanNet/ScanNet to get access to the ScanNet dataset. Our method relies on the .ply as well as the .labels.ply files.
Start a new training:
python train_wrapper.py \ -c PATH_TO_EXPERIMENTS_FILE.json
Resume a training:
python train_wrapper.py \ -c PATH_TO_EXPERIMENTS_FILE.json \ -r PATH_TO_CHECKPOINT.pth
Reproduce the scores of our paper:
python run.py \ -c experiments/EXPERIMENT_NAME.json \ -r paper_checkpoints/EXPERIMENT_NAME.pth \ -e