This is a PyTorch implementation of the paper "Reinforcement Learning-Based Black-Box Model Inversion Attacks" accepted by CVPR 2023.

This code has been tested with Python 3.8.8, PyTorch 1.8.0 and cuda 10.2.89.

Model weights for experiments can be downloaded from the link below. https://drive.google.com/drive/folders/15Xcqoz53TQVUUyZe9HNtchoCriLUeQ-O?usp=sharing

Please check the commands included in run_experiments.sh. There are commands for both the simplified experiment and the experiments reported in the paper.

Please run

bash run_experiments.sh

to reproduce the results.

[04.28] Mistakes made during code cleanup have been fixed.

This repository contains code snippets and some model weights from repositories mentioned below.

https://github.com/MKariya1998/GMI-Attack

https://github.com/SCccc21/Knowledge-Enriched-DMI

https://github.com/BY571/Soft-Actor-Critic-and-Extensions