5 citations · 7 across the 7 of their papers we have counts for
8 papers
SyncGait: Robust Long-Distance Authentication for Drone Delivery via Implicit Gait Behaviors
Zijian Ling, Man Zhou, Hongda Zhai +5
In recent years, drone delivery, which utilizes unmanned aerial vehicles (UAVs) for package delivery and pickup, has gradually emerged as a crucial method in logistics. Since deliv…
T2I-Based Physical-World Appearance Attack against Traffic Sign Recognition Systems in Autonomous Driving
Chen Ma, Ningfei Wang, Junhao Zheng +4
Traffic Sign Recognition (TSR) systems play a critical role in Autonomous Driving (AD) systems, enabling real-time detection of road signs, such as STOP and speed limit signs. Whil…
Revisiting Adversarial Patch Defenses on Object Detectors: Unified Evaluation, Large-Scale Dataset, and New Insights
Junhao Zheng, Jiahao Sun, Chenhao Lin +6
Developing reliable defenses against patch attacks on object detectors has attracted increasing interest. However, we identify that existing defense evaluations lack a unified and…
Concept Unlearning by Modeling Key Steps of Diffusion Process
Chaoshuo Zhang, Chenhao Lin, Zhengyu Zhao +3
Text-to-image diffusion models remain susceptible to generating undesirable or harmful content. Although concept unlearning mitigates this risk, existing methods struggle with a cr…
Prediction Inconsistency Helps Achieve Generalizable Detection of Adversarial Examples
Sicong Han, Chenhao Lin, Zhengyu Zhao +6
Adversarial detection protects models from adversarial attacks by refusing suspicious test samples. However, current detection methods often suffer from weak generalization: their…
A Survey of Defenses Against AI-Generated Visual Media: Detection,Disruption, and Authentication
Jingyi Deng, Chenhao Lin, Zhengyu Zhao +4
Deep generative models have demonstrated impressive performance in various computer vision applications, including image synthesis, video generation, and medical analysis. Despite…
ControlLoc: Physical-World Hijacking Attack on Visual Perception in Autonomous Driving
Chen Ma, Ningfei Wang, Zhengyu Zhao +3
Recent research in adversarial machine learning has focused on visual perception in Autonomous Driving (AD) and has shown that printed adversarial patches can attack object detecto…
Revisiting Transferable Adversarial Images: Systemization, Evaluation, and New Insights
Zhengyu Zhao, Hanwei Zhang, Renjue Li +6
Transferable adversarial images raise critical security concerns for computer vision systems in real-world, black-box attack scenarios. Although many transfer attacks have been pro…