The following publications are possibly variants of this publication:
- Adversarial Watermarking to Attack Deep Neural NetworksGengxing Wang, Xinyuan Chen, Chang Xu. icassp 2019: 1962-1966 [doi]
- Stronger and Faster Wasserstein Adversarial AttacksKaiwen Wu, Allen Houze Wang, Yaoliang Yu. icml 2020: 10377-10387 [doi]
- Geometrically Invariant Watermark Using Fast Correlation AttacksDan Wang, Peizhong Lu. iih-msp 2006: 465-468 [doi]
- Robust Adversarial Watermark Defending Against GAN Synthesization AttackShengwang Xu, Tong Qiao, Ming Xu 0001, Wei Wang 0025, Ning Zheng 0001. spl, 31:351-355, 2024. [doi]
- A Watermarking-Based Framework for Protecting Deep Image Classifiers Against Adversarial AttacksChen Sun, En-Hui Yang. cvpr 2021: 3329-3338 [doi]
- Watermarking-based Defense against Adversarial Attacks on Deep Neural NetworksXiaoting Li, Lingwei Chen, Jinquan Zhang, James Larus, Dinghao Wu. ijcnn 2021: 1-8 [doi]
- Sample Based Fast Adversarial Attack MethodZhi-Ming Wang, Meng-Ting Gu, Jia-Hui Hou. npl, 50(3):2731-2744, 2019. [doi]
- Adversarial attacks on Faster R-CNN object detectorYutong Wang, Kunfeng Wang, Zhanxing Zhu, Feiyue Wang 0001. ijon, 382:87-95, 2020. [doi]