Understanding Robustness of Transformers for Image Classification

26 March 2021

Srinadh Bhojanapalli

Papers citing "Understanding Robustness of Transformers for Image Classification"

36 / 86 papers shown

Title
Self-Supervised Learning for Videos: A Survey Madeline Chantry Schiappa Y. S. Rawat M. Shah SSL 36 131 0 18 Jun 2022
One-Pixel Shortcut: on the Learning Preference of Deep Neural Networks Shutong Wu Sizhe Chen Cihang Xie X. Huang AAML 45 27 0 24 May 2022
Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging Yuanhao Cai Jing Lin Haoqian Wang Xin Yuan Henghui Ding Yulun Zhang Radu Timofte Luc Van Gool 80 116 0 20 May 2022
It's DONE: Direct ONE-shot learning with quantile weight imprinting Kazufumi Hosoda Keigo Nishida S. Seno Tomohiro Mashita H. Kashioka I. Ohzawa 24 2 0 28 Apr 2022
Deeper Insights into the Robustness of ViTs towards Common Corruptions Rui Tian Zuxuan Wu Qi Dai Han Hu Yu-Gang Jiang ViT AAML 21 4 0 26 Apr 2022
Does Robustness on ImageNet Transfer to Downstream Tasks? Yutaro Yamada Mayu Otani OOD 32 27 0 08 Apr 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 30 32 0 25 Mar 2022
InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding Hanrong Ye Dan Xu ViT 21 84 0 15 Mar 2022
Joint rotational invariance and adversarial training of a dual-stream Transformer yields state of the art Brain-Score for Area V4 William Berrios Arturo Deza MedIm ViT 30 13 0 08 Mar 2022
3D Common Corruptions and Data Augmentation Oğuzhan Fatih Kar Teresa Yeo Andrei Atanov Amir Zamir 3DPC 45 107 0 02 Mar 2022
How Do Vision Transformers Work? Namuk Park Songkuk Kim ViT 47 465 0 14 Feb 2022
Are Transformers More Robust? Towards Exact Robustness Verification for Transformers B. Liao Chih-Hong Cheng Hasan Esen Alois Knoll AAML 26 1 0 08 Feb 2022
Transformers in Self-Supervised Monocular Depth Estimation with Unknown Camera Intrinsics Arnav Varma Hemang Chawla Bahram Zonooz Elahe Arani ViT MDE 36 49 0 07 Feb 2022
GLPanoDepth: Global-to-Local Panoramic Depth Estimation Jia-Chi Bai Shuichang Lai Haoyu Qin Jie Guo Yanwen Guo ViT MDE 69 21 0 06 Feb 2022
Query Efficient Decision Based Sparse Attacks Against Black-Box Deep Learning Models Viet Vo Ehsan Abbasnejad D. Ranasinghe AAML 30 14 0 31 Jan 2022
Video Transformers: A Survey Javier Selva A. S. Johansen Sergio Escalera Kamal Nasrollahi T. Moeslund Albert Clapés ViT 22 103 0 16 Jan 2022
Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal Yucheng Shi Yahong Han Yu-an Tan Xiaohui Kuang 38 30 0 07 Dec 2021
DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation Lukas Hoyer Dengxin Dai Luc Van Gool AI4CE 36 450 0 29 Nov 2021
OOD-CV: A Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images Bingchen Zhao Shaozuo Yu Wufei Ma M. Yu Shenxiao Mei Angtian Wang Ju He Alan Yuille Adam Kortylewski 31 53 0 29 Nov 2021
Are Vision Transformers Robust to Patch Perturbations? Jindong Gu Volker Tresp Yao Qin AAML ViT 38 60 0 20 Nov 2021
Discrete Representations Strengthen Vision Transformer Robustness Chengzhi Mao Lu Jiang Mostafa Dehghani Carl Vondrick Rahul Sukthankar Irfan Essa ViT 27 43 0 20 Nov 2021
Are Transformers More Robust Than CNNs? Yutong Bai Jieru Mei Alan Yuille Cihang Xie ViT AAML 192 257 0 10 Nov 2021
Are we ready for a new paradigm shift? A Survey on Visual Deep MLP Ruiyang Liu Hai-Tao Zheng Li Tao Dun Liang Haitao Zheng 85 97 0 07 Nov 2021
Blending Anti-Aliasing into Vision Transformer Shengju Qian Hao Shao Yi Zhu Mu Li Jiaya Jia 26 20 0 28 Oct 2021
Adversarial Token Attacks on Vision Transformers Ameya Joshi Gauri Jagatap C. Hegde ViT 30 19 0 08 Oct 2021
Adversarial Robustness Comparison of Vision Transformer and MLP-Mixer to CNNs Philipp Benz Soomin Ham Chaoning Zhang Adil Karjauv In So Kweon AAML ViT 47 78 0 06 Oct 2021
Do Vision Transformers See Like Convolutional Neural Networks? M. Raghu Thomas Unterthiner Simon Kornblith Chiyuan Zhang Alexey Dosovitskiy ViT 67 924 0 19 Aug 2021
Exploring Corruption Robustness: Inductive Biases in Vision Transformers and MLP-Mixers Katelyn Morrison B. Gilby Colton Lipchak Adam Mattioli Adriana Kovashka ViT 28 17 0 24 Jun 2021
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning Liangqiong Qu Yuyin Zhou Paul Pu Liang Yingda Xia Feifei Wang Ehsan Adeli L. Fei-Fei D. Rubin FedML AI4CE 19 175 0 10 Jun 2021
Reveal of Vision Transformers Robustness against Adversarial Attacks Ahmed Aldahdooh W. Hamidouche Olivier Déforges ViT 15 56 0 07 Jun 2021
Intriguing Properties of Vision Transformers Muzammal Naseer Kanchana Ranasinghe Salman Khan Munawar Hayat Fahad Shahbaz Khan Ming-Hsuan Yang ViT 265 621 0 21 May 2021
Vision Transformers are Robust Learners Sayak Paul Pin-Yu Chen ViT 28 304 0 17 May 2021
MLP-Mixer: An all-MLP Architecture for Vision Ilya O. Tolstikhin N. Houlsby Alexander Kolesnikov Lucas Beyer Xiaohua Zhai ... Andreas Steiner Daniel Keysers Jakob Uszkoreit Mario Lucic Alexey Dosovitskiy 274 2,606 0 04 May 2021
Transformers in Vision: A Survey Salman Khan Muzammal Naseer Munawar Hayat Syed Waqas Zamir Fahad Shahbaz Khan M. Shah ViT 227 2,430 0 04 Jan 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 264 4,489 0 23 Jan 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 950 20,567 0 17 Apr 2017