AFM is a novel gray-box adversarial attack using flow matching to create visually imperceptible perturbations that degrade performance of Vision-Language-Action and modular end-to-end autonomous driving models while showing strong cross-model transferability.
Physical 3d adversarial attacks against monocular depth estimation in autonomous driving,
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Adversarial Flow Matching for Imperceptible Attacks on End-to-End Autonomous Driving
AFM is a novel gray-box adversarial attack using flow matching to create visually imperceptible perturbations that degrade performance of Vision-Language-Action and modular end-to-end autonomous driving models while showing strong cross-model transferability.