We propose the adversarial blur attack (ABA) against visual object tracking. The ICCV link: https://arxiv.org/abs/2107.12085 and, https://openaccess.thecvf.com/content/ICCV2021/papers/Guo_Learning_To_Adversarially_Blur_Visual_Object_Tracking_ICCV_2021_paper.pdf
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Our implementation is based on PySOT, You need to follow their installation steps for environment setup.
You can enter the target tracker's directory in the experiments folder, run the attack/evaluate experiment with the following command:
# attack
CUDA_VISIBLE_DEVICES=0 python -u ../../tools/attack_test.py --snapshot model.pth --dataset OTB100 --config config.yaml
CUDA_VISIBLE_DEVICES=0 python -u ../../tools/attack_dimp.py --snapshot model.pth --dataset OTB100 --config config.yaml
CUDA_VISIBLE_DEVICES=0 python -u ../../tools/attack_kys.py --snapshot model.pth --dataset OTB100 --config config.yaml
# evaluate
python ../../tools/eval.py --tracker_path ./results --dataset OTB100 --num 10 --tracker_prefix 'cl'
python ../../tools/eval.py --tracker_path ./results --dataset VOT2018 --num 10 --tracker_prefix 'clean'
python ../../tools/eval.py --tracker_path ./results --dataset UAV --num 10 --tracker_prefix 'guo'
python ../../tools/eval.py --tracker_path ./results --dataset VOT2019 --num 10--tracker_prefix 'csa'@inproceedings{guo2021learning,
title={Learning to Adversarially Blur Visual Object Tracking},
author={Qing Guo and Ziyi Cheng and Felix Juefei-Xu and Lei Ma and Xiaofei Xie and Yang Liu and Jianjun Zhao},
year={2021},
booktitle={ICCV}
}