9 citations · 10 across the 3 of their papers we have counts for
5 papers
Detectors Learn the Wrong Thing: Shortcut-Resistant Adversarial Training Against Physically Realizable Attacks
Yuanhao Huang, Yilong Ren, Jinlei Wang +3
AI-enabled visual perception systems are increasingly deployed in intelligent transportation infrastructure and autonomous vehicle related applications. However, physically realiza…
AdvSerial: Physical Adversarial Attacks on Infrastructure-mounted Pedestrian Detectors via Semantic Feature Suppression
Yuanhao Huang, Yilong Ren, Jinlei Wang +3
AI-based visual perception systems are increasingly deployed in infrastructure surveillance, including roadside monitoring units, highway cameras, and smart-city pedestrian managem…
AdvReal: Physical Adversarial Patch Generation Framework for Security Evaluation of Object Detection Systems
Yuanhao Huang, Yilong Ren, Jinlei Wang +4
Autonomous vehicles are typical complex intelligent systems with artificial intelligence at their core. However, perception methods based on deep learning are extremely vulnerable…
Text2Scenario: Text-Driven Scenario Generation for Autonomous Driving Test
Xuan Cai, Xuesong Bai, Zhiyong Cui +4
Autonomous driving (AD) testing constitutes a critical methodology for assessing performance benchmarks prior to product deployment. The creation of segmented scenarios within a si…
VCAT: Vulnerability-aware and Curiosity-driven Adversarial Training for Enhancing Autonomous Vehicle Robustness
Xuan Cai, Zhiyong Cui, Xuesong Bai +4
Autonomous vehicles (AVs) face significant threats to their safe operation in complex traffic environments. Adversarial training has emerged as an effective method of enabling AVs…