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Explainability and Robustness in Metric Space

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Explainability and Robustness in Metric Space

This repository implements explainability and robustness methods such as Saliency Maps, Integrated Gradients, FGSM and PGD Attacks applied to point cloud classification models.

Installation

  • Set up and activate conda environment.
conda env create -f environment.yml
conda activate erms
  • Install pre-commit hooks.
pre-commit install
  • Download pretrained checkpoint.
mkdir out
gdown --no-cookies --id 1-2UrF5V_gpjGNbWfbk_kEp742Bnjlnc- -O out/pointmlp.pth

Quick Start

  • Run all experiments and plot results.
python run.py