[CVPR2020] On Isometry Robustness of Deep 3D Point Cloud Models under Adversarial Attacks

April 8, 2020 ยท View on GitHub

Environment

Ubuntu 16.04.5 LTS
GPU RTX2080ti
Python 3.7
Install the python dependencies with

pip install -r requirements.txt

Data

  • [ModelNet40] automatically downloaded
  • [ShapeNet] /fxia22/pointnet.pytorch (follow the guidence for downloading)
    The default path of data is '/data'.

Usage Sample

Train model

With default parameters setting, run

python train.py --data modelnet40 --model pointnet

Trained model is stored in '/checkpoints' with log in '/logs_train'.

Launch attack

If you don't want to retrain the model, download a trained model here (with ModelNet40 data, PointNet model), move it to '/checkpoints', then run

python attack.py --data modelnet40 --model pointnet --model_path 'example'

The attack log is stored in '/logs_attack'. The attack is default to be CTRI since TSI is done at the same time.

Supplementary materials

Please check here for supplementary materials mentioned in this paper.

References