Fooling a Real Car with Adversarial Traffic Signs

30 June 2019

Papers citing "Fooling a Real Car with Adversarial Traffic Signs"

38 / 38 papers shown

Title
PaniCar: Securing the Perception of Advanced Driving Assistance Systems Against Emergency Vehicle Lighting Elad Feldman Jacob Shams Dudi Biton Alfred Chen Shaoyuan Xie Satoru Koda Yisroel Mirsky A. Shabtai Yuval Elovici Ben Nassi AAML 82 0 0 08 May 2025
Towards Fair Class-wise Robustness: Class Optimal Distribution Adversarial Training Hongxin Zhi Hongtao Yu Shaome Li Xiuming Zhao Yiteng Wu OOD 73 0 0 08 Jan 2025
Learning Fair Robustness via Domain Mixup Meiyu Zhong Ravi Tandon OOD 122 0 0 21 Nov 2024
DFT-Based Adversarial Attack Detection in MRI Brain Imaging: Enhancing Diagnostic Accuracy in Alzheimer's Case Studies Mohammad Hossein Najafi Mohammad Morsali Mohammadmahdi Vahediahmar Saeed Bagheri Shouraki AAML MedIm 98 0 0 16 Aug 2024
Adversarial Safety-Critical Scenario Generation using Naturalistic Human Driving Priors Kunkun Hao Yonggang Luo Wen Cui Yuqiao Bai Jucheng Yang Songyang Yan Yuxi Pan Zijiang Yang AAML 94 20 0 06 Aug 2024
Steal Now and Attack Later: Evaluating Robustness of Object Detection against Black-box Adversarial Attacks Erh-Chung Chen Pin-Yu Chen I-Hsin Chung Che-Rung Lee AAML 67 2 0 24 Apr 2024
Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness David Fernández Llorca Ronan Hamon Henrik Junklewitz Kathrin Grosse Lars Kunze ... Nick Reed Alexandre Alahi Emilia Gómez Ignacio E. Sánchez Á. Kriston 108 5 0 21 Feb 2024
Attacking Motion Planners Using Adversarial Perception Errors Jonathan Sadeghi Nicholas A. Lord John Redford Romain Mueller AAML 79 2 0 21 Nov 2023
Explainable and Trustworthy Traffic Sign Detection for Safe Autonomous Driving: An Inductive Logic Programming Approach Zahra Chaghazardi Saber Fallah Alireza Tamaddoni-Nezhad AAML 74 3 0 30 Aug 2023
Adversarial Attacks on Traffic Sign Recognition: A Survey Svetlana Pavlitska Nico Lambing J. Marius Zöllner AAML 88 18 0 17 Jul 2023
Distribution-restrained Softmax Loss for the Model Robustness Hao Wang Chen Li Jinzhe Jiang Xin Zhang Yaqian Zhao Weifeng Gong OOD 94 2 0 22 Mar 2023
Towards Understanding and Boosting Adversarial Transferability from a Distribution Perspective Yao Zhu YueFeng Chen Xiaodan Li Kejiang Chen Yuan He Xiang Tian Bo Zheng Yao-wu Chen Qingming Huang AAML 64 59 0 09 Oct 2022
A Survey on Physical Adversarial Attack in Computer Vision Donghua Wang Wen Yao Tingsong Jiang Guijian Tang Xiaoqian Chen AAML 151 39 0 28 Sep 2022
Semantic Preserving Adversarial Attack Generation with Autoencoder and Genetic Algorithm Xinyi Wang S. Y. Enoch Dan Dongseong Kim AAML 34 2 0 25 Aug 2022
Exact Spectral Norm Regularization for Neural Networks Anton Johansson Claes Strannegård Niklas Engsner P. Mostad AAML 70 2 0 27 Jun 2022
Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples Dongyoon Yang Insung Kong Yongdai Kim OOD AAML 80 10 0 07 Jun 2022
Holistic Approach to Measure Sample-level Adversarial Vulnerability and its Utility in Building Trustworthy Systems Gaurav Kumar Nayak Ruchit Rawal Rohit Lal Himanshu Patil Anirban Chakraborty AAML 58 2 0 05 May 2022
Scalable Whitebox Attacks on Tree-based Models Giuseppe Castiglione G. Ding Masoud Hashemi C. Srinivasa Ga Wu AAML 25 1 0 31 Mar 2022
bAdvertisement: Attacking Advanced Driver-Assistance Systems Using Print Advertisements Ben Nassi Jacob Shams Raz Ben-Netanel Yuval Elovici AAML 34 4 0 21 Feb 2022
Unreasonable Effectiveness of Last Hidden Layer Activations for Adversarial Robustness Ömer Faruk Tuna Ferhat Ozgur Catak M. T. Eskil AAML 35 4 0 15 Feb 2022
Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial Examples Against Traffic Sign Recognition Systems Wei Jia Zhaojun Lu Haichun Zhang Zhenglin Liu Jie Wang Gang Qu AAML 71 54 0 17 Jan 2022
ZeBRA: Precisely Destroying Neural Networks with Zero-Data Based Repeated Bit Flip Attack Dahoon Park K. Kwon Sunghoon Im Jaeha Kung AAML 48 3 0 01 Nov 2021
Optical Adversarial Attack Abhiram Gnanasambandam A. Sherman Stanley H. Chan AAML 118 67 0 13 Aug 2021
Dealing with Adversarial Player Strategies in the Neural Network Game iNNk through Ensemble Learning Mathias Löwe Jennifer Villareale Evan Freed Aleksanteri Sladek Jichen Zhu S. Risi AAML 61 5 0 05 Jul 2021
Towards interpreting computer vision based on transformation invariant optimization Chen Li Jinzhe Jiang Xin Zhang Tonghuan Zhang Yaqian Zhao Dong-Liang Jiang Rengang Li AI4CE 24 0 0 18 Jun 2021
Adaptive Clustering of Robust Semantic Representations for Adversarial Image Purification S. Silva Arun Das I. Scarff Peyman Najafirad AAML 52 1 0 05 Apr 2021
Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey Thomas Rojat Raphael Puget David Filliat Javier Del Ser R. Gelin Natalia Díaz Rodríguez XAI AI4TS 99 135 0 02 Apr 2021
Exploiting epistemic uncertainty of the deep learning models to generate adversarial samples Ömer Faruk Tuna Ferhat Ozgur Catak M. T. Eskil AAML 90 33 0 08 Feb 2021
Explainability of deep vision-based autonomous driving systems: Review and challenges Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 186 177 0 13 Jan 2021
Closeness and Uncertainty Aware Adversarial Examples Detection in Adversarial Machine Learning Ömer Faruk Tuna Ferhat Ozgur Catak M. T. Eskil AAML 83 11 0 11 Dec 2020
Generating Out of Distribution Adversarial Attack using Latent Space Poisoning Ujjwal Upadhyay Prerana Mukherjee 78 7 0 09 Dec 2020
Experiments in Autonomous Driving Through Imitation Learning Michael Muratov Abdulwasay Mehar W. Lee Michael Szpakowicz Ose Edmond Umolu Joshua Mazariegos Bobadilla Ali Kuwajerwala SSL 52 1 0 25 Nov 2020
AI Governance for Businesses Johannes Schneider Rene Abraham Christian Meske Jan vom Brocke AI4TS 108 70 0 20 Nov 2020
To be Robust or to be Fair: Towards Fairness in Adversarial Training Han Xu Xiaorui Liu Yaxin Li Anil K. Jain Jiliang Tang 70 181 0 13 Oct 2020
Double Targeted Universal Adversarial Perturbations Philipp Benz Chaoning Zhang Tooba Imtiaz In So Kweon AAML 95 48 0 07 Oct 2020
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey S. Silva Peyman Najafirad AAML OOD 104 135 0 01 Jul 2020
Safety Concerns and Mitigation Approaches Regarding the Use of Deep Learning in Safety-Critical Perception Tasks Oliver Willers Sebastian Sudholt Shervin Raafatnia Stephanie Abrecht 106 80 0 22 Jan 2020
Simple iterative method for generating targeted universal adversarial perturbations Hokuto Hirano Kazuhiro Takemoto AAML 100 32 0 15 Nov 2019