Comdefend: An efficient image compression model to defend adversarial examples X Jia, X Wei, X Cao, H Foroosh Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 334 | 2019 |
LAS-AT: adversarial training with learnable attack strategy X Jia, Y Zhang, B Wu, K Ma, J Wang, X Cao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 164 | 2022 |
Adv-watermark: A novel watermark perturbation for adversarial examples X Jia, X Wei, X Cao, X Han Proceedings of the 28th ACM international conference on multimedia, 1579-1587, 2020 | 86 | 2020 |
Defending against model stealing via verifying embedded external features Y Li, L Zhu, X Jia, Y Jiang, ST Xia, X Cao AAAI 2022, 2022 | 73 | 2022 |
Boosting fast adversarial training with learnable adversarial initialization X Jia, Y Zhang, B Wu, J Wang, X Cao IEEE Transactions on Image Processing 31, 4417-4430, 2022 | 62 | 2022 |
Prior-Guided Adversarial Initialization for Fast Adversarial Training X Jia, Y Zhang, X Wei, B Wu, K Ma, J Wang, X Cao ECCV 2022, 2022 | 44 | 2022 |
Generating transferable 3d adversarial point cloud via random perturbation factorization B He, J Liu, Y Li, S Liang, J Li, X Jia, X Cao Proceedings of the AAAI Conference on Artificial Intelligence 37 (1), 764-772, 2023 | 37 | 2023 |
A Large-scale Multiple-objective Method for Black-box Attack against Object Detection S Liang, L Li, Y Fan, X Jia, J Li, B Wu, X Cao ECCV 2022, 2022 | 35 | 2022 |
Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal X Liu, J Liu, Y Bai, J Gu, T Chen, X Jia, X Cao ECCV 2022, 2022 | 27 | 2022 |
Improving fast adversarial training with prior-guided knowledge X Jia, Y Zhang, X Wei, B Wu, K Ma, J Wang, X Cao IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 26 | 2024 |
A mutation-based method for multi-modal jailbreaking attack detection X Zhang, C Zhang, T Li, Y Huang, X Jia, X Xie, Y Liu, C Shen arXiv preprint arXiv:2312.10766, 2023 | 26 | 2023 |
A survey on transferability of adversarial examples across deep neural networks J Gu, X Jia, P de Jorge, W Yu, X Liu, A Ma, Y Xun, A Hu, A Khakzar, Z Li, ... arXiv preprint arXiv:2310.17626, 2023 | 26 | 2023 |
Sa-attack: Improving adversarial transferability of vision-language pre-training models via self-augmentation B He, X Jia, S Liang, T Lou, Y Liu, X Cao arXiv preprint arXiv:2312.04913, 2023 | 24 | 2023 |
Context-aware robust fine-tuning X Mao, Y Chen, X Jia, R Zhang, H Xue, Z Li International Journal of Computer Vision 132 (5), 1685-1700, 2024 | 20 | 2024 |
Poisoned forgery face: Towards backdoor attacks on face forgery detection J Liang, S Liang, A Liu, X Jia, J Kuang, X Cao arXiv preprint arXiv:2402.11473, 2024 | 20 | 2024 |
Identifying and resisting adversarial videos using temporal consistency X Jia, X Wei, X Cao arXiv preprint arXiv:1909.04837, 2019 | 18 | 2019 |
Ot-attack: Enhancing adversarial transferability of vision-language models via optimal transport optimization D Han, X Jia, Y Bai, J Gu, Y Liu, X Cao arXiv preprint arXiv:2312.04403, 2023 | 17 | 2023 |
Does few-shot learning suffer from backdoor attacks? X Liu, X Jia, J Gu, Y Xun, S Liang, X Cao Proceedings of the AAAI Conference on Artificial Intelligence 38 (18), 19893 …, 2024 | 14 | 2024 |
Hide in thicket: Generating imperceptible and rational adversarial perturbations on 3d point clouds T Lou, X Jia, J Gu, L Liu, S Liang, B He, X Cao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 14 | 2024 |
Improved techniques for optimization-based jailbreaking on large language models X Jia, T Pang, C Du, Y Huang, J Gu, Y Liu, X Cao, M Lin arXiv preprint arXiv:2405.21018, 2024 | 12 | 2024 |