Similarity Distribution based Membership Inference Attack on Person Re-Identification (AAAI oral 2023 )
This is the pytorch implementation of the paper (accepted by AAAI oarl 2023).
GPU: RTX3090
CUDA: 12.0
Python: 3.8.3
torch: 1.8.0+cu111
os: Ubuntu 18.04
install sklearn
pip install scikit-learn
Step 1: Gaining the feature embedding outputs of training and test set from the target model.
Step 2: Training and evaluating the model.
python main.py
If you use this code or the models in your research, please give credit to the following papers:
@inproceedings{GaoJZYD0MDZ23,
author = {Junyao Gao and
Xinyang Jiang and
Huishuai Zhang and
Yifan Yang and
Shuguang Dou and
Dongsheng Li and
Duoqian Miao and
Cheng Deng and
Cairong Zhao},
title = {Similarity Distribution Based Membership Inference Attack on Person
Re-identification},
booktitle = {Thirty-Seventh {AAAI} Conference on Artificial Intelligence, {AAAI}},
pages = {14820--14828},
publisher = {{AAAI} Press},
year = {2023},
}