Awesome

One simple code to cheat your retrieval model via Modifying Query ONLY (based on pytorch) accepted by IJCV. Pre-print version is at https://arxiv.org/abs/1809.02681.

The main idea underpinning our method is simple yet effective, making the query feature to conduct a U-turn :arrow_right_hook:.

Table of contents

• Re-ID Attacking
• Image Retrieval Attacking
• Cifar Attacking

Re-ID Attacking

1.1 Preparing your reID models.

Please check the step-by-step tutorial in https://github.com/layumi/Person_reID_baseline_pytorch

1.2 Attacking Market-1501

Try four attack methods with one line. Please change the path before run it.

python experiment.py

Image Retrieval Attacking

2.1 Download the pre-trained model on Oxford and Paris

We attach the training code, which is based on the excellent code in TPAMI 2018. https://github.com/layumi/Oxford-Paris-Attack

2.2 Attacking the Oxford and Paris Dataset

Our effort is to cheat the TPAMI model. Yes. We succeed. https://github.com/layumi/Oxford-Paris-Attack

2.3 Attacking Food-256 and CUB-200-2011

Please check subfolders.

Food: https://github.com/layumi/U_turn/tree/master/Food

CUB: https://github.com/layumi/U_turn/tree/master/cub

Cifar Attacking

3.1 Cifar (ResNet-Wide)

We attach the training code, which is borrowed from ResNet-Wide (with Random Erasing).

3.2 Attacking Cifar

https://github.com/layumi/A_reID/tree/master/cifar

Citation

@article{zheng2022query,
  title={U-turn: Crafting Adversarial Queries with Opposite-direction Features},
  author={Zheng, Zhedong and Zheng, Liang and Yang, Yi and Wu, Fei},
  journal={IJCV},
  year={2022}
}