3 papers
cs.CV2025
A Single Set of Adversarial Clothes Breaks Multiple Defense Methods in the Physical World
Wei Zhang, Zhanhao Hu, Xiao Li +2
In recent years, adversarial attacks against deep learning-based object detectors in the physical world have attracted much attention. To defend against these attacks, researchers…
cs.CV2025
PBCAT: Patch-based composite adversarial training against physically realizable attacks on object detection
Xiao Li, Yiming Zhu, Yifan Huang +4
Object detection plays a crucial role in many security-sensitive applications. However, several recent studies have shown that object detectors can be easily fooled by physically r…
cs.CR2024
Perfect Gradient Inversion in Federated Learning: A New Paradigm from the Hidden Subset Sum Problem
Qiongxiu Li, Lixia Luo, Agnese Gini +6
Federated Learning (FL) has emerged as a popular paradigm for collaborative learning among multiple parties. It is considered privacy-friendly because local data remains on persona…