Xiaogeng Liu

Towards Efficient Data-Centric Robust Machine Learning with Noise-based Augmentation

Shengshan Hu, Fangzhou Wu, Haoyu Wang, 2022, ArXiv.

Protecting Facial Privacy: Generating Adversarial Identity Masks via Style-robust Makeup Transfer

Minghui Li, Shengshan Hu, L. Zhang, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

AdvHash: Set-to-set Targeted Attack on Deep Hashing with One Single Adversarial Patch

Shengshan Hu, Minghui Li, Hai Jin, 2021, ACM Multimedia.

Detecting Backdoors During the Inference Stage Based on Corruption Robustness Consistency

Minghui Li, Chaowei Xiao, Shengshan Hu, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Why Does Little Robustness Help? Understanding and Improving Adversarial Transferability from Surrogate Training

Minghui Li, Shengshan Hu, L. Zhang, 2023, 2307.07873.

Towards Understanding Adversarial Transferability From Surrogate Training

Minghui Li, Shengshan Hu, L. Zhang, 2023 .

Why Does Little Robustness Help? Understanding Adversarial Transferability From Surrogate Training

Minghui Li, Shengshan Hu, L. Zhang, 2023, ArXiv.

Why Does Little Robustness Help? Understanding and Improving Adversarial Transferability from Surrogate Training

Minghui Li, Shengshan Hu, Wei Wan, 2023, 2307.07873.