ICML 2020 adversarial paper list
CVPR 2020 adversarial paper list
Cihang Xie, Zhishuai Zhang, Yuyin Zhou, Song Bai, Jianyu Wang, Zhou Ren, and Alan L Yuille. Improving transferability of adversarial examples with input diversity. CVPR 2019.
Jiadong Lin, Chuanbiao Song, Kun He, Liwei Wang, John E. Hopcroft. Nesterov Accelerated Gradient and Scale Invariance for Improving Transferability of Adversarial Examples. arXiv Preprint arXiv:1908.06281 2019.
Runtian Zhai, Tianle Cai, Di He, Chen Dan, Kun He, John Hopcroft and Liwei Wang. Adversarially Robust Generalization Just Requires More Unlabeled Data. arXiv Preprint arXiv:1906.00555.
Yair Carmon, Aditi Raghunathan, Ludwig Schmidt, Percy Liang and John C. Duchi. Unlabeled Data Improves Adversarial Robustness. arXiv Preprint arXiv:1905.13736.
Jonathan Uesato, Jean-Baptiste Alayrac, Po-Sen Huang, Robert Stanforth, Alhussein Fawzi and Pushmeet Kohli. Are Labels Required for Improving Adversarial Robustness?. arXiv Preprint arXiv:1905.13725.
Alvin Chan, Yi Tay, Yew Soon Ong and Jie Fu. Jacobian Adversarially Regularized Networks for Robustness. ICLR 2020.
Haohan Wang, Xindi Wu, Zeyi Huang, Eric P. Xing. High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks. CVPR 2020.