| Perceptual-Sensitive GAN for Generating Adversarial Patches A Liu, X Liu, J Fan, Y Ma, A Zhang, H Xie, D Tao The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, 2019 | 275 | 2019 |
| Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World J Wang, A Liu, Z Yin, S Liu, S Tang, X Liu IEEE Conference on Computer Vision and Pattern Recognition, 2021 | 148 | 2021 |
| Bias-based Universal Adversarial Patch Attack for Automatic Check-out A Liu, J Wang, X Liu, C Zhang, B Cao, H Yu European Conference on Computer Vision 2020, 2020 | 122 | 2020 |
| Training robust deep neural networks via adversarial noise propagation A Liu, X Liu, H Yu, C Zhang, Q Liu, D Tao IEEE Transactions on Image Processing, 2021 | 93 | 2021 |
| Interpreting and improving adversarial robustness with neuron sensitivity C Zhang, A Liu, X Liu, Y Xu, H Yu, Y Ma, T Li IEEE Transactions on Image Processing, 2020 | 93 | 2020 |
| Robustart: Benchmarking robustness on architecture design and training techniques S Tang, R Gong, Y Wang, A Liu, J Wang, X Chen, F Yu, X Liu, D Song, ... arXiv preprint arXiv:2109.05211, 2021 | 89 | 2021 |
| BiBERT: Accurate Fully Binarized BERT H Qin, Y Ding, M Zhang, Q Yan, A Liu, Q Dang, Z Liu, X Liu International Conference on Learning Representations, ICLR 2022, 2022 | 70 | 2022 |
| Spatiotemporal Attacks for Embodied Agents A Liu, T Huang, X Liu, Y Xu, Y Ma, X Chen, SJ Maybank, D Tao European Conference on Computer Vision 2020, 2020 | 63 | 2020 |
| Coarse-to-Fine Image Inpainting via Region-wise Convolutions and Non-Local Correlation M Yuqing, L Xianglong, B Shihao, W Lei, H Dailan, L Aishan The Twenty-Eighth International Joint Conference on Artificial Intelligence …, 2019 | 59* | 2019 |
| Transductive Relation-Propagation Network for Few-shot Learning XZ Yuqing Ma, Shihao Bai, Shan An, Wei Liu, Aishan Liu, Xianglong Liu International Joint Conference on Artificial Intelligence --Pacific Rim …, 2020 | 52* | 2020 |
| Regionwise generative adversarial image inpainting for large missing areas Y Ma, X Liu, S Bai, L Wang, A Liu, D Tao, ER Hancock IEEE transactions on cybernetics, 2022 | 36 | 2022 |
| X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detection A Liu, J Guo, J Wang, S Liang, R Tao, W Zhou, C Liu, X Liu, D Tao USENIX Security Symposium 2023, 2023 | 35 | 2023 |
| Universal adversarial patch attack for automatic checkout using perceptual and attentional bias J Wang, A Liu, X Bai, X Liu IEEE Transactions on Image Processing 31, 598-611, 2021 | 31 | 2021 |
| Harnessing Perceptual Adversarial Patches for Crowd Counting S Liu, J Wang, A Liu, Y Li, Y Gao, X Liu, D Tao ACM CCS 2022, 2021 | 30 | 2021 |
| A comprehensive evaluation framework for deep model robustness J Guo, W Bao, J Wang, Y Ma, X Gao, G Xiao, A Liu, J Dong, X Liu, W Wu Pattern Recognition 137, 109308, 2023 | 29 | 2023 |
| Defensive patches for robust recognition in the physical world J Wang, Z Yin, P Hu, A Liu, R Tao, H Qin, X Liu, D Tao Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 25 | 2022 |
| Towards defending multiple Lp-norm bounded adversarial perturbations via gated batch normalization A Liu, S Tang, X Chen, L Huang, H Qin, X Liu, D Tao International Journal of Computer Vision, 2023 | 24* | 2023 |
| Understanding Adversarial Robustness via Critical Attacking Route XX Tianlin Li, Aishan Liu, Xianglong Liu, Yitao Xu, Chongzhi Zhang Information Sciences, 2020 | 24* | 2020 |
| Over-sampling de-occlusion attention network for prohibited items detection in noisy x-ray images R Tao, Y Wei, H Li, A Liu, Y Ding, H Qin, X Liu arXiv preprint arXiv:2103.00809, 2021 | 23 | 2021 |
| Generating transferable adversarial examples against vision transformers Y Wang, J Wang, Z Yin, R Gong, J Wang, A Liu, X Liu Proceedings of the 30th ACM International Conference on Multimedia, 5181-5190, 2022 | 18 | 2022 |
Dacheng TaoNanyang Technological University在 ntu.edu.sg 的电子邮件经过验证
