Robustifying Token Attention for Vision Transformers

Robustifying Token Attention for Vision Transformers

20 March 2023

Bernt Schiele

Papers citing "Robustifying Token Attention for Vision Transformers"

10 / 10 papers shown

Title
Enhancing Layer Attention Efficiency through Pruning Redundant Retrievals Hanze Li Xiande Huang 39 0 0 09 Mar 2025
One Diffusion Step to Real-World Super-Resolution via Flow Trajectory Distillation J. Li Jiezhang Cao Yong Guo W. J. Li Yulun Zhang DiffM 73 0 0 04 Feb 2025
Benchmarking the Robustness of Temporal Action Detection Models Against Temporal Corruptions Runhao Zeng Xiaoyong Chen Jiaming Liang Huisi Wu Guangzhong Cao Yong Guo AAML 32 3 0 29 Mar 2024
Improving Robustness by Enhancing Weak Subnets Yong Guo David Stutz Bernt Schiele AAML 14 15 0 30 Jan 2022
Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal Yucheng Shi Yahong Han Yu-an Tan Xiaohui Kuang 35 26 0 07 Dec 2021
Are Transformers More Robust Than CNNs? Yutong Bai Jieru Mei Alan Yuille Cihang Xie ViT AAML 181 257 0 10 Nov 2021
Intriguing Properties of Vision Transformers Muzammal Naseer Kanchana Ranasinghe Salman Khan Munawar Hayat F. Khan Ming-Hsuan Yang ViT 251 618 0 21 May 2021
Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions Wenhai Wang Enze Xie Xiang Li Deng-Ping Fan Kaitao Song Ding Liang Tong Lu Ping Luo Ling Shao ViT 263 3,604 0 24 Feb 2021
Evolving Attention with Residual Convolutions Yujing Wang Yaming Yang Jiangang Bai Mingliang Zhang Jing Bai J. Yu Ce Zhang Gao Huang Yunhai Tong ViT 24 32 0 20 Feb 2021
Transformers in Vision: A Survey Salman Khan Muzammal Naseer Munawar Hayat Syed Waqas Zamir F. Khan M. Shah ViT 225 2,427 0 04 Jan 2021