no code implementations • 28 Oct 2022 • Ching Lam Choi, Farzan Farnia
Despite their great success in image recognition tasks, deep neural networks (DNNs) have been observed to be susceptible to universal adversarial perturbations (UAPs) which perturb all input samples with a single perturbation vector.
no code implementations • 27 Apr 2021 • Yixiao Ge, Xiao Zhang, Ching Lam Choi, Ka Chun Cheung, Peipei Zhao, Feng Zhu, Xiaogang Wang, Rui Zhao, Hongsheng Li
In this way, our BAKE framework achieves online knowledge ensembling across multiple samples with only a single network.
1 code implementation • CVPR 2021 • Rui Liu, Yixiao Ge, Ching Lam Choi, Xiaogang Wang, Hongsheng Li
Conditional generative adversarial networks (cGANs) target at synthesizing diverse images given the input conditions and latent codes, but unfortunately, they usually suffer from the issue of mode collapse.