Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

16 March 2022

Papers citing "Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?"

16 / 16 papers shown

Title
Don't Lag, RAG: Training-Free Adversarial Detection Using RAG Roie Kazoom Raz Lapid Moshe Sipper Ofer Hadar VLM ObjD AAML 52 0 0 07 Apr 2025
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers Haoyang Liu Aditya Singh Yijiang Li Haohan Wang AAML ViT 31 1 0 15 Mar 2024
Attacking Transformers with Feature Diversity Adversarial Perturbation Chenxing Gao Hang Zhou Junqing Yu Yuteng Ye Jiale Cai Junle Wang Wei Yang AAML 27 3 0 10 Mar 2024
What Makes Pre-Trained Visual Representations Successful for Robust Manipulation? Kaylee Burns Zach Witzel Jubayer Ibn Hamid Tianhe Yu Chelsea Finn Karol Hausman OOD SSL 20 22 0 03 Nov 2023
Investigating the Robustness and Properties of Detection Transformers (DETR) Toward Difficult Images Zhao Ning Zou Yuhang Zhang Robert Wijaya 13 0 0 12 Oct 2023
Random Position Adversarial Patch for Vision Transformers Mingzhen Shao ViT AAML 14 2 0 09 Jul 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 30 48 0 18 May 2023
Inference Time Evidences of Adversarial Attacks for Forensic on Transformers Hugo Lemarchant Liang Li Yiming Qian Yuta Nakashima Hajime Nagahara ViT AAML 25 0 0 31 Jan 2023
On the interplay of adversarial robustness and architecture components: patches, convolution and attention Francesco Croce Matthias Hein 37 6 0 14 Sep 2022
Exploring Adversarial Robustness of Vision Transformers in the Spectral Perspective Gihyun Kim Juyeop Kim Jong-Seok Lee AAML ViT 6 4 0 20 Aug 2022
Self-Ensembling Vision Transformer (SEViT) for Robust Medical Image Classification Faris Almalik Mohammad Yaqub Karthik Nandakumar ViT AAML MedIm 10 33 0 04 Aug 2022
Towards Efficient Adversarial Training on Vision Transformers Boxi Wu Jindong Gu Zhifeng Li Deng Cai Xiaofei He Wei Liu ViT AAML 23 37 0 21 Jul 2022
Give Me Your Attention: Dot-Product Attention Considered Harmful for Adversarial Patch Robustness Giulio Lovisotto Nicole Finnie Mauricio Muñoz Chaithanya Kumar Mummadi J. H. Metzen AAML ViT 17 32 0 25 Mar 2022
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 295 5,761 0 29 Apr 2021
VidTr: Video Transformer Without Convolutions Yanyi Zhang Xinyu Li Chunhui Liu Bing Shuai Yi Zhu Biagio Brattoli Hao Chen I. Marsic Joseph Tighe ViT 136 193 0 23 Apr 2021
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 243 914 0 21 Apr 2018