Cheating Stereo Matching in Full-scale: Physical Adversarial Attack against Binocular Depth Estimation in Autonomous Driving

Researchers have developed the first physical adversarial attack targeting stereo-based depth estimation in autonomous vehicles, using 3D camouflaged objects that can fool binocular vision systems. The attack employs global texture patterns and a novel merging technique to create nearly invisible threats that cause stereo matching models to produce incorrect depth information.