Yingzhe He — accepted AI-conference papers

2025

ADBM: Adversarial Diffusion Bridge Model for Reliable Adversarial Purification

Xiao Li, Wenxuan Sun, Huanran Chen, Qiongxiu Li, Yingzhe He, Jie Shi +1

ICLR 2025poster

Recently Diffusion-based Purification (DiffPure) has been recognized as an effective defense method against adversarial examples. However, we find DiffPure which directly employs the original pre-trained diffusion models for adversarial purification, to be suboptimal. This is due to an inherent trad…

Cited by 6 Source ↗PDF ↗code ↗Scholar ↗

2025

PBCAT: Patch-Based Composite Adversarial Training against Physically Realizable Attacks on Object Detection

Xiao Li, Yiming Zhu, Yifan Huang, Wei Zhang, Yingzhe He, Jie Shi +1

ICCV 2025poster

Object detection plays a crucial role in many security-sensitive applications, such as autonomous driving and video surveillance. However, several recent studies have shown that object detectors can be easily fooled by physically realizable attacks, e.g., adversarial patches and recent adversarial t…

Cited by 0 Source ↗PDF ↗Scholar ↗