| Adversarial Texture for Fooling Person Detectors in the Physical World Z Hu, S Huang, X Zhu, F Sun, B Zhang, X Hu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 85 | 2022 |
| Infrared Invisible Clothing: Hiding from Infrared Detectors at Multiple Angles in Real World X Zhu, Z Hu, S Huang, J Li, X Hu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 43 | 2022 |
| An stdp-based supervised learning algorithm for spiking neural networks Z Hu, T Wang, X Hu Neural Information Processing: 24th International Conference, ICONIP 2017 …, 2017 | 12 | 2017 |
| Physically Realizable Natural-Looking Clothing Textures Evade Person Detectors via 3D Modeling Z Hu, W Chu, X Zhu, H Zhang, B Zhang, X Hu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 8 | 2023 |
| Language-Driven Anchors for Zero-Shot Adversarial Robustness X Li, W Zhang, Y Liu, Z Hu, B Zhang, X Hu arXiv preprint arXiv:2301.13096, 2023 | 4* | 2023 |
| On the privacy effect of data enhancement via the lens of memorization X Li, Q Li, Z Hu, X Hu IEEE Transactions on Information Forensics and Security, 2024 | 3 | 2024 |
| Hiding from infrared detectors in real world with adversarial clothes X Zhu, Z Hu, S Huang, J Li, X Hu, Z Wang Applied Intelligence 53 (23), 29537-29555, 2023 | 1 | 2023 |
| Amplification trojan network: Attack deep neural networks by amplifying their inherent weakness Z Hu, J Zhu, B Zhang, X Hu Neurocomputing 505, 142-153, 2022 | 1 | 2022 |
| Driving into Danger: Adversarial Patch Attack on End-to-End Autonomous Driving Systems Using Deep Learning T Wang, X Kuang, H Li, Q Du, Z Hu, H Deng, G Zhao 2023 IEEE Symposium on Computers and Communications (ISCC), 995-1000, 2023 | | 2023 |
