Enhancing Adversarial Robustness via Anomaly-aware Adversarial Training. - Keke Tang; Tianrui Lou; Xu He; Yawen Shi; Peican Zhu; Zhaoquan Gu (KSEM (1), 2023)

SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation. - Bangyan He; Xiaojun Jia; Siyuan Liang; Tianrui Lou; Yang Liu 003; Xiaochun Cao (CoRR, 2023)

Medical personal protective equipment detection based on attention mechanism and multi-scale fusion. - Jianlou Lou; Xiangyu Li; Guang Huo; Feng Liang; Zhaoyang Qu; Tianrui Lou; Ndagijimana Kwihangano Soleil (Int. J. Sens. Networks, 2023)

Rethinking Perturbation Directions for Imperceptible Adversarial Attacks on Point Clouds. - Keke Tang; Yawen Shi; Tianrui Lou; Weilong Peng; Xu He; Peican Zhu; Zhaoquan Gu; Zhihong Tian (IEEE Internet Things J., 2023)

Hide in Thicket: Generating Imperceptible and Rational Adversarial Perturbations on 3D Point Clouds. - Tianrui Lou; Xiaojun Jia; Jindong Gu; Li Liu 002; Siyuan Liang; Bangyan He; Xiaochun Cao (CVPR, 2024)

Effective Single-Step Adversarial Training With Energy-Based Models. - Keke Tang; Tianrui Lou; Weilong Peng; Nenglun Chen; Yawen Shi; Wenping Wang 001 (IEEE Trans. Emerg. Top. Comput. Intell., 2024)

3D Gaussian Splatting Driven Multi-View Robust Physical Adversarial Camouflage Generation. - Tianrui Lou; Xiaojun Jia; Siyuan Liang; Jiawei Liang; Ming Zhang; Yanjun Xiao; Xiaochun Cao (CoRR, 2025)