Adversarial Patch

27 December 2017

Justin Gilmer

Papers citing "Adversarial Patch"

50 / 241 papers shown

Title
Visually Imperceptible Adversarial Patch Attacks on Digital Images Yaguan Qian Jiamin Wang Bin Wang Xiang Ling Zhaoquan Gu Chunming Wu Wassim Swaileh AAML 39 2 0 02 Dec 2020
A Study on the Uncertainty of Convolutional Layers in Deep Neural Networks Hao Shen Sihong Chen Ran Wang 30 5 0 27 Nov 2020
Invisible Perturbations: Physical Adversarial Examples Exploiting the Rolling Shutter Effect Athena Sayles Ashish Hooda M. Gupta Rahul Chatterjee Earlence Fernandes AAML 19 76 0 26 Nov 2020
Adversarial Attack on Facial Recognition using Visible Light Morgan Frearson Kien Nguyen AAML 21 7 0 25 Nov 2020
Adversarial Attacks on Optimization based Planners Sai H. Vemprala Ashish Kapoor AAML 29 12 0 30 Oct 2020
Dynamic Adversarial Patch for Evading Object Detection Models Shahar Hoory T. Shapira A. Shabtai Yuval Elovici AAML 18 40 0 25 Oct 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 234 680 0 19 Oct 2020
Double Targeted Universal Adversarial Perturbations Philipp Benz Chaoning Zhang Tooba Imtiaz In So Kweon AAML 40 48 0 07 Oct 2020
Generating Adversarial yet Inconspicuous Patches with a Single Image Jinqi Luo Tao Bai Jun Zhao AAML 27 6 0 21 Sep 2020
MultAV: Multiplicative Adversarial Videos Shao-Yuan Lo Vishal M. Patel AAML 26 8 0 17 Sep 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 41 62 0 11 Sep 2020
Defending Against Multiple and Unforeseen Adversarial Videos Shao-Yuan Lo Vishal M. Patel AAML 31 23 0 11 Sep 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 33 156 0 08 Sep 2020
Adversarial Patch Camouflage against Aerial Detection Ajaya Adhikari R. D. Hollander I. Tolios M. V. Bekkum Anneloes M. Bal ... Dennis Gross N. Jansen Guillermo A. Pérez Kit Buurman S. Raaijmakers AAML 29 43 0 31 Aug 2020
AP-Loss for Accurate One-Stage Object Detection Kean Chen Weiyao Lin Jianguo Li John See Ji Wang Junni Zou ObjD 22 66 0 17 Aug 2020
A Survey on Security Attacks and Defense Techniques for Connected and Autonomous Vehicles M. Pham Kaiqi Xiong 25 138 0 16 Jul 2020
SLAP: Improving Physical Adversarial Examples with Short-Lived Adversarial Perturbations Giulio Lovisotto H.C.M. Turner Ivo Sluganovic Martin Strohmeier Ivan Martinovic AAML 19 101 0 08 Jul 2020
ConFoc: Content-Focus Protection Against Trojan Attacks on Neural Networks Miguel Villarreal-Vasquez B. Bhargava AAML 17 38 0 01 Jul 2020
Proper Network Interpretability Helps Adversarial Robustness in Classification Akhilan Boopathy Sijia Liu Gaoyuan Zhang Cynthia Liu Pin-Yu Chen Shiyu Chang Luca Daniel AAML FAtt 27 66 0 26 Jun 2020
Backdoor Attacks Against Deep Learning Systems in the Physical World Emily Wenger Josephine Passananti A. Bhagoji Yuanshun Yao Haitao Zheng Ben Y. Zhao AAML 31 200 0 25 Jun 2020
PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking Chong Xiang A. Bhagoji Vikash Sehwag Prateek Mittal AAML 30 29 0 17 May 2020
Blind Backdoors in Deep Learning Models Eugene Bagdasaryan Vitaly Shmatikov AAML FedML SILM 46 298 0 08 May 2020
Adversarial Training against Location-Optimized Adversarial Patches Sukrut Rao David Stutz Bernt Schiele AAML 19 91 0 05 May 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Xia Hu AAML 26 8 0 23 Apr 2020
Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning Michael Everett Bjorn Lutjens Jonathan P. How AAML 13 41 0 11 Apr 2020
ObjectNet Dataset: Reanalysis and Correction Ali Borji 3DPC 13 11 0 04 Apr 2020
Generating Socially Acceptable Perturbations for Efficient Evaluation of Autonomous Vehicles Songan Zhang H. Peng S. Nageshrao E. Tseng AAML 27 5 0 18 Mar 2020
Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles Ranjie Duan Xingjun Ma Yisen Wang James Bailey •. A. K. Qin Yun Yang AAML 167 224 0 08 Mar 2020
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence S. Raschka Joshua Patterson Corey J. Nolet AI4CE 24 484 0 12 Feb 2020
Attacking Optical Character Recognition (OCR) Systems with Adversarial Watermarks Lu Chen Wenyuan Xu AAML 21 21 0 08 Feb 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 28 80 0 22 Jan 2020
A Little Fog for a Large Turn Harshitha Machiraju V. Balasubramanian AAML 15 9 0 16 Jan 2020
Exploring Adversarial Attack in Spiking Neural Networks with Spike-Compatible Gradient Ling Liang Xing Hu Lei Deng Yujie Wu Guoqi Li Yufei Ding Peng Li Yuan Xie AAML 22 60 0 01 Jan 2020
Design and Interpretation of Universal Adversarial Patches in Face Detection Xiao Yang Fangyun Wei Hongyang R. Zhang Jun Zhu AAML CVBM 52 43 0 30 Nov 2019
Fine-grained Synthesis of Unrestricted Adversarial Examples Omid Poursaeed Tianxing Jiang Yordanos Goshu Harry Yang Serge J. Belongie Ser-Nam Lim AAML 37 13 0 20 Nov 2019
Generate (non-software) Bugs to Fool Classifiers Hiromu Yakura Youhei Akimoto Jun Sakuma AAML 25 10 0 20 Nov 2019
Simple iterative method for generating targeted universal adversarial perturbations Hokuto Hirano Kazuhiro Takemoto AAML 27 30 0 15 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 18 104 0 13 Nov 2019
Imperceptible Adversarial Attacks on Tabular Data Vincent Ballet X. Renard Jonathan Aigrain Thibault Laugel P. Frossard Marcin Detyniecki 12 72 0 08 Nov 2019
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey Olakunle Ibitoye Rana Abou-Khamis Mohamed el Shehaby Ashraf Matrawy M. O. Shafiq AAML 37 68 0 06 Nov 2019
Feature relevance quantification in explainable AI: A causal problem Dominik Janzing Lenon Minorics Patrick Blobaum FAtt CML 13 278 0 29 Oct 2019
Understanding and Quantifying Adversarial Examples Existence in Linear Classification Xupeng Shi A. Ding AAML 14 3 0 27 Oct 2019
Attacking Optical Flow Anurag Ranjan J. Janai Andreas Geiger Michael J. Black AAML 3DPC 16 87 0 22 Oct 2019
Learning Model-Agnostic Counterfactual Explanations for Tabular Data Martin Pawelczyk Johannes Haug Klaus Broelemann Gjergji Kasneci OOD CML 33 199 0 21 Oct 2019
Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms Z. Q. Lin M. Shafiee S. Bochkarev Michael St. Jules Xiao Yu Wang A. Wong FAtt 29 80 0 16 Oct 2019
Defending Neural Backdoors via Generative Distribution Modeling Ximing Qiao Yukun Yang H. Li AAML 21 183 0 10 Oct 2019
Role of Spatial Context in Adversarial Robustness for Object Detection Aniruddha Saha Akshayvarun Subramanya Koninika Patil Hamed Pirsiavash ObjD AAML 32 53 0 30 Sep 2019
Defending Against Physically Realizable Attacks on Image Classification Tong Wu Liang Tong Yevgeniy Vorobeychik AAML 22 125 0 20 Sep 2019
Towards Quality Assurance of Software Product Lines with Adversarial Configurations Paul Temple M. Acher Gilles Perrouin Battista Biggio J. Jézéquel Fabio Roli AAML 16 11 0 16 Sep 2019
Universal Physical Camouflage Attacks on Object Detectors Lifeng Huang Chengying Gao Yuyin Zhou Cihang Xie Alan Yuille C. Zou Ning Liu AAML 143 162 0 10 Sep 2019