ARIA: Adversarially Robust Image Attribution for Content Provenance

25 February 2022

Maksym Andriushchenko

Papers citing "ARIA: Adversarially Robust Image Attribution for Content Provenance"

50 / 57 papers shown

Title
Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash Lukas Struppek Dominik Hintersdorf Daniel Neider Kristian Kersting MIACV 45 48 0 12 Nov 2021
VPN: Video Provenance Network for Robust Content Attribution Alexander Black Tu Bui Simon Jenni Vishy Swaminathan John Collomosse 60 9 0 21 Sep 2021
OSCAR-Net: Object-centric Scene Graph Attention for Image Attribution Eric N. D. Nguyen Tu Bui Vishy Swaminathan John Collomosse 30 15 0 07 Aug 2021
Can contrastive learning avoid shortcut solutions? Joshua Robinson Li Sun Ke Yu Kayhan Batmanghelich Stefanie Jegelka S. Sra SSL 47 143 0 21 Jun 2021
Class-Aware Robust Adversarial Training for Object Detection Pin-Chun Chen Bo-Han Kung Jun-Cheng Chen AAML ObjD 86 48 0 30 Mar 2021
Deepfake Forensics via An Adversarial Game Zhi Wang Yiwen Guo W. Zuo AAML 32 36 0 25 Mar 2021
On the effectiveness of adversarial training against common corruptions Klim Kireev Maksym Andriushchenko Nicolas Flammarion AAML 33 103 0 03 Mar 2021
Exploring Adversarial Robustness of Deep Metric Learning Thomas Kobber Panum Zehao Wang Pengyu Kan Earlence Fernandes S. Jha AAML 37 7 0 14 Feb 2021
Understanding and Achieving Efficient Robustness with Adversarial Supervised Contrastive Learning Anh-Vu Bui Trung Le He Zhao Paul Montague S. Çamtepe Dinh Q. Phung AAML 21 14 0 25 Jan 2021
Adversarial Momentum-Contrastive Pre-Training Cong Xu Dan Li Min Yang SSL 29 15 0 24 Dec 2020
Adversarial collision attacks on image hashing functions Brian Dolhansky Cristian Canton Ferrer AAML 79 20 0 18 Nov 2020
Robust Pre-Training by Adversarial Contrastive Learning Ziyu Jiang Tianlong Chen Ting-Li Chen Zhangyang Wang 64 230 0 26 Oct 2020
Contrastive Learning with Adversarial Examples Chih-Hui Ho Nuno Vasconcelos SSL 36 142 0 22 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 268 689 0 19 Oct 2020
Viewmaker Networks: Learning Views for Unsupervised Representation Learning Alex Tamkin Mike Wu Noah D. Goodman SSL 79 64 0 14 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 34 327 0 07 Oct 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor Aleksander Madry 51 423 0 16 Jul 2020
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification Francisco Utrera Evan Kravitz N. Benjamin Erichson Rekha Khanna Michael W. Mahoney GAN 40 33 0 11 Jul 2020
Understanding and Improving Fast Adversarial Training Maksym Andriushchenko Nicolas Flammarion AAML 50 286 0 06 Jul 2020
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization Dan Hendrycks Steven Basart Norman Mu Saurav Kadavath Frank Wang ... Samyak Parajuli Mike Guo D. Song Jacob Steinhardt Justin Gilmer OOD 252 1,715 0 29 Jun 2020
Bootstrap your own latent: A new approach to self-supervised Learning Jean-Bastien Grill Florian Strub Florent Altché Corentin Tallec Pierre Harvey Richemond ... M. G. Azar Bilal Piot Koray Kavukcuoglu Rémi Munos Michal Valko SSL 260 6,718 0 13 Jun 2020
Adversarial Self-Supervised Contrastive Learning Minseon Kim Jihoon Tack Sung Ju Hwang SSL 49 249 0 13 Jun 2020
Targeted Attack for Deep Hashing based Retrieval Jiawang Bai Bin Chen Yiming Li Dongxian Wu Weiwei Guo Shutao Xia En-Hui Yang AAML 68 85 0 15 Apr 2020
Evading Deepfake-Image Detectors with White- and Black-Box Attacks Nicholas Carlini Hany Farid AAML 31 147 0 01 Apr 2020
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning Tianlong Chen Sijia Liu Shiyu Chang Yu Cheng Lisa Amini Zhangyang Wang AAML 35 247 0 28 Mar 2020
RAFT: Recurrent All-Pairs Field Transforms for Optical Flow Zachary Teed Jia Deng MDE 181 2,583 0 26 Mar 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 181 1,821 0 03 Mar 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 69 794 0 26 Feb 2020
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger Jingfeng Zhang Xilie Xu Bo Han Gang Niu Li-zhen Cui Masashi Sugiyama Mohan S. Kankanhalli AAML 45 400 0 26 Feb 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 186 18,523 0 13 Feb 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 118 1,167 0 12 Jan 2020
Adversarial Examples Improve Image Recognition Cihang Xie Mingxing Tan Boqing Gong Jiang Wang Alan Yuille Quoc V. Le AAML 63 564 0 21 Nov 2019
Momentum Contrast for Unsupervised Visual Representation Learning Kaiming He Haoqi Fan Yuxin Wu Saining Xie Ross B. Girshick SSL 99 11,959 0 13 Nov 2019
An Alternative Surrogate Loss for PGD-based Adversarial Testing Sven Gowal J. Uesato Chongli Qin Po-Sen Huang Timothy A. Mann Pushmeet Kohli AAML 78 89 0 21 Oct 2019
Metric Learning for Adversarial Robustness Chengzhi Mao Ziyuan Zhong Junfeng Yang Carl Vondrick Baishakhi Ray OOD 55 185 0 03 Sep 2019
Targeted Mismatch Adversarial Attack: Query with a Flower to Retrieve the Tower Giorgos Tolias Filip Radenovic Ondřej Chum AAML 29 70 0 24 Aug 2019
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty Dan Hendrycks Mantas Mazeika Saurav Kadavath D. Song OOD SSL 31 940 0 28 Jun 2019
Detecting Photoshopped Faces by Scripting Photoshop Sheng-Yu Wang Oliver Wang Andrew Owens Richard Y. Zhang Alexei A. Efros CVBM PICV 44 135 0 13 Jun 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 80 1,825 0 06 May 2019
Fooling automated surveillance cameras: adversarial patches to attack person detection Simen Thys W. V. Ranst Toon Goedemé AAML 92 567 0 18 Apr 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 105 3,399 0 28 Mar 2019
Adversarial Examples Are a Natural Consequence of Test Error in Noise Nic Ford Justin Gilmer Nicholas Carlini E. D. Cubuk AAML 58 319 0 29 Jan 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty Dan Hendrycks Kimin Lee Mantas Mazeika NoLa 59 726 0 28 Jan 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 94 2,525 0 24 Jan 2019
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 73 1,772 0 30 May 2018
ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector Shang-Tse Chen Cory Cornelius Jason Martin Duen Horng Chau ObjD 179 425 0 16 Apr 2018
Adversarial Patch Tom B. Brown Dandelion Mané Aurko Roy Martín Abadi Justin Gilmer AAML 54 1,093 0 27 Dec 2017
Note on Attacking Object Detectors with Adversarial Stickers Kevin Eykholt Ivan Evtimov Earlence Fernandes Yue Liu D. Song Tadayoshi Kohno Amir Rahmati A. Prakash Florian Tramèr AAML 43 36 0 21 Dec 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 213 11,962 0 19 Jun 2017
Mask R-CNN Kaiming He Georgia Gkioxari Piotr Dollár Ross B. Girshick ObjD 298 27,018 0 20 Mar 2017