Universal Adversarial Directions

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.

Self-distillation with Batch Knowledge Ensembling Improves ImageNet Classification

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.

Classification General Classification +1

DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial 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.

Contrastive Learning Generative Adversarial Network +1