Attacking Motion Planners Using Adversarial Perception Errors

21 November 2023

Papers citing "Attacking Motion Planners Using Adversarial Perception Errors"

8 / 8 papers shown

Title
EMPERROR: A Flexible Generative Perception Error Model for Probing Self-Driving Planners Niklas Hanselmann Simon Doll Marius Cordts Hendrik P. A. Lensch Andreas Geiger 39 0 0 12 Nov 2024
Preprocessors Matter! Realistic Decision-Based Attacks on Machine Learning Systems Chawin Sitawarin Florian Tramèr Nicholas Carlini AAML 70 8 0 07 Oct 2022
Risk-Driven Design of Perception Systems Anthony Corso Sydney M. Katz Craig Innes Xin Du S. Ramamoorthy Mykel J. Kochenderfer 18 8 0 21 May 2022
Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review Xinhai Zhang Jianbo Tao Kaige Tan Martin Törngren José Manuel Gaspar Sánchez ... Magnus Gyllenhammar F. Wotawa N. Mohan Mihai Nica Hermann Felbinger 27 39 0 16 Oct 2021
A Step Towards Efficient Evaluation of Complex Perception Tasks in Simulation Jonathan Sadeghi Blaine Rogers James Gunn Thomas Saunders Sina Samangooei P. Dokania John Redford 26 8 0 28 Sep 2021
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems Aman Sinha Matthew O'Kelly Russ Tedrake John C. Duchi 33 46 0 24 Aug 2020
ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector Shang-Tse Chen Cory Cornelius Jason Martin Duen Horng Chau ObjD 145 424 0 16 Apr 2018
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 250 5,830 0 08 Jul 2016