49 citations · 172 across the 13 of their papers we have counts for
5 papers · 1 filter
You Can't See Me: Physical Removal Attacks on LiDAR-based Autonomous Vehicles Driving Frameworks
Yulong Cao, S. Hrushikesh Bhupathiraju, Pirouz Naghavi +3
Autonomous Vehicles (AVs) increasingly use LiDAR-based object detection systems to perceive other vehicles and pedestrians on the road. While existing attacks on LiDAR-based autono…
PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition
Jiachen Sun, Weili Nie, Zhiding Yu +2
3D Point cloud is becoming a critical data representation in many real-world applications like autonomous driving, robotics, and medical imaging. Although the success of deep learn…
A Cooperative Perception Environment for Traffic Operations and Control
Hanlin Chen, Brian Liu, Xumiao Zhang +3
Existing data collection methods for traffic operations and control usually rely on infrastructure-based loop detectors or probe vehicle trajectories. Connected and automated vehic…
Robust Trajectory Prediction against Adversarial Attacks
Yulong Cao, Danfei Xu, Xinshuo Weng +4
Trajectory prediction using deep neural networks (DNNs) is an essential component of autonomous driving (AD) systems. However, these methods are vulnerable to adversarial attacks,…
Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions
Jiachen Sun, Qingzhao Zhang, Bhavya Kailkhura +3
Deep neural networks on 3D point cloud data have been widely used in the real world, especially in safety-critical applications. However, their robustness against corruptions is le…