Title
$GenderBias-\emph{VL}: Benchmarking Gender Bias in Vision Language Models via Counterfactual Probing$ GenderBias-\emph{VL}: Benchmarking Gender Bias in Vision Language Models via Counterfactual Probing Yisong Xiao Aishan Liu QianJia Cheng Zhenfei Yin Siyuan Liang Jiapeng Li Jing Shao Xianglong Liu Dacheng Tao 26 4 0 30 Jun 2024
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
On the unreasonable vulnerability of transformers for image restoration -- and an easy fix Shashank Agnihotri Kanchana Vaishnavi Gandikota Julia Grabinski Paramanand Chandramouli M. Keuper 19 8 0 25 Jul 2023
On the Importance of Backbone to the Adversarial Robustness of Object Detectors Xiao-Li Li Hang Chen Xiaolin Hu AAML 34 4 0 27 May 2023
Latent Imitator: Generating Natural Individual Discriminatory Instances for Black-Box Fairness Testing Yisong Xiao Aishan Liu Tianlin Li Xianglong Liu 17 25 0 19 May 2023
Benchmarking the Robustness of Quantized Models Yisong Xiao Tianyuan Zhang Shunchang Liu Haotong Qin AAML MQ 22 2 0 08 Apr 2023
A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking Chang-Shu Liu Yinpeng Dong Wenzhao Xiang X. Yang Hang Su Junyi Zhu YueFeng Chen Yuan He H. Xue Shibao Zheng OOD VLM AAML 15 72 0 28 Feb 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min-Bin Lin Weiwei Liu Shuicheng Yan DiffM 14 206 0 09 Feb 2023
CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion Zixiang Zhao Hao Bai Jiangshe Zhang Yulun Zhang Shuang Xu Zudi Lin Radu Timofte Luc Van Gool 17 303 0 26 Nov 2022
Improving Robust Fairness via Balance Adversarial Training Chunyu Sun Chenye Xu Chengyuan Yao Siyuan Liang Yichao Wu Ding Liang XiangLong Liu Aishan Liu 11 11 0 15 Sep 2022
Bag of Tricks for FGSM Adversarial Training Zichao Li Li Liu Zeyu Wang Yuyin Zhou Cihang Xie AAML 14 6 0 06 Sep 2022
An Impartial Take to the CNN vs Transformer Robustness Contest Francesco Pinto Philip H. S. Torr P. Dokania UQCV AAML 9 47 0 22 Jul 2022
Towards Efficient Adversarial Training on Vision Transformers Boxi Wu Jindong Gu Zhifeng Li Deng Cai Xiaofei He Wei Liu ViT AAML 21 37 0 21 Jul 2022
Fault-Tolerant Deep Learning: A Hierarchical Perspective Cheng Liu Zhen Gao Siting Liu Xuefei Ning Huawei Li Xiaowei Li 15 9 0 05 Apr 2022
ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches Maura Pintor Daniele Angioni Angelo Sotgiu Luca Demetrio Ambra Demontis Battista Biggio Fabio Roli AAML 17 50 0 07 Mar 2022
Are Transformers More Robust Than CNNs? Yutong Bai Jieru Mei Alan Yuille Cihang Xie ViT AAML 170 256 0 10 Nov 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 44 100 0 07 Oct 2021
Intriguing Properties of Vision Transformers Muzammal Naseer Kanchana Ranasinghe Salman Khan Munawar Hayat F. Khan Ming-Hsuan Yang ViT 248 618 0 21 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 239 2,554 0 04 May 2021
RepVGG: Making VGG-style ConvNets Great Again Xiaohan Ding X. Zhang Ningning Ma Jungong Han Guiguang Ding Jian-jun Sun 117 1,484 0 11 Jan 2021
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 207 668 0 19 Oct 2020
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 261 10,106 0 16 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 250 5,813 0 08 Jul 2016