3 citations · 3 across the 7 of their papers we have counts for
7 papers
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…
FlyTrap: Physical Distance-Pulling Attack Towards Camera-based Autonomous Target Tracking Systems
Shaoyuan Xie, Mohamad Habib Fakih, Junchi Lu +6
Autonomous Target Tracking (ATT) systems, especially ATT drones, are widely used in applications such as surveillance, border control, and law enforcement, while also being misused…
Revisiting Physical-World Adversarial Attack on Traffic Sign Recognition: A Commercial Systems Perspective
Ningfei Wang, Shaoyuan Xie, Takami Sato +3
Traffic Sign Recognition (TSR) is crucial for safe and correct driving automation. Recent works revealed a general vulnerability of TSR models to physical-world adversarial attacks…
SlowPerception: Physical-World Latency Attack against Visual Perception in Autonomous Driving
Chen Ma, Ningfei Wang, Zhengyu Zhao +2
Autonomous Driving (AD) systems critically depend on visual perception for real-time object detection and multiple object tracking (MOT) to ensure safe driving. However, high laten…
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…
SlowTrack: Increasing the Latency of Camera-based Perception in Autonomous Driving Using Adversarial Examples
Chen Ma, Ningfei Wang, Qi Alfred Chen +1
In Autonomous Driving (AD), real-time perception is a critical component responsible for detecting surrounding objects to ensure safe driving. While researchers have extensively ex…
Intriguing Properties of Diffusion Models: An Empirical Study of the Natural Attack Capability in Text-to-Image Generative Models
Takami Sato, Justin Yue, Nanze Chen +2
Denoising probabilistic diffusion models have shown breakthrough performance to generate more photo-realistic images or human-level illustrations than the prior models such as GANs…