This repository is for SPE-Net: Boosting Point Cloud Analysis via Rotation Robustness Enhancement. The repository is based on the open-source codebase Detectron2 and CloserLook3D.
- Linux with Python ≥ 3.6
- PyTorch ≥ 1.8
- fvcore
- pycocotools
- Java 1.8.0
- Prepare the target dataset following the instructions from the codebase CloserLook3D, and put the pre-processed data in the folder
./dataset
. - Run pytorchpoints/init.sh to compile the C++ code.
configs/spe_net_modelnet40_so3.yaml is the config file for training SPE-Net model on ModelNet40. Run script python3 train_net.py --num-gpus 4 --config-file configs/spe_net_modelnet40_so3.yaml
.
pytorchpoints/modeling/backbones/resnet.py includes the implementation for SPE-Net overall architecture.
pytorchpoints/modeling/local_aggregation/spe_mlp.py includes the implementation for SPE-MLP.
Thanks the contribution of Detectron2, CloserLook3D and the PyTorch team.