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08/30/2023
Intriguing Properties of Diffusion Models: A Large-Scale Dataset for Evaluating Natural Attack Capability in Text-to-Image Generative Models
Denoising probabilistic diffusion models have shown breakthrough perform...
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08/23/2023
Does Physical Adversarial Example Really Matter to Autonomous Driving? Towards System-Level Effect of Adversarial Object Evasion Attack
In autonomous driving (AD), accurate perception is indispensable to achi...
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03/19/2023
Revisiting LiDAR Spoofing Attack Capabilities against Object Detection: Improvements, Measurement, and New Attack
LiDAR (Light Detection And Ranging) is an indispensable sensor for preci...
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03/09/2023
Learning Representation for Anomaly Detection of Vehicle Trajectories
Predicting the future trajectories of surrounding vehicles based on thei...
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05/27/2022
Semi-supervised Semantics-guided Adversarial Training for Trajectory Prediction
Predicting the trajectories of surrounding objects is a critical task in...
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03/31/2022
Towards Driving-Oriented Metric for Lane Detection Models
After the 2017 TuSimple Lane Detection Challenge, its dataset and evalua...
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07/06/2021
On Robustness of Lane Detection Models to Physical-World Adversarial Attacks in Autonomous Driving
After the 2017 TuSimple Lane Detection Challenge, its evaluation based o...
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02/27/2021
End-to-end Uncertainty-based Mitigation of Adversarial Attacks to Automated Lane Centering
In the development of advanced driver-assistance systems (ADAS) and auto...
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09/14/2020
Hold Tight and Never Let Go: Security of Deep Learning based Automated Lane Centering under Physical-World Attack
Automated Lane Centering (ALC) systems are convenient and widely deploye...
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03/03/2020