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Exploring the Landscape of Spatial Robustness

7 December 2017

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Papers citing "Exploring the Landscape of Spatial Robustness"

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Title
ROSA: Addressing text understanding challenges in photographs via ROtated SAmpling Hernán Maina Guido Ivetta Mateo Lione Stuto Julian Martin Eisenschlos Jorge Sánchez Luciana Benotti 51 0 0 04 Jun 2025
Instruct2Attack: Language-Guided Semantic Adversarial Attacks Jiang-Long Liu Chen Wei Yuxiang Guo Heng Yu Alan Yuille Soheil Feizi Chun Pong Lau Rama Chellappa DiffM AAML 95 7 0 27 Nov 2023
Invariance Measures for Neural Networks F. Quiroga J. Torrents-Barrena Laura Lanzarini Domenec Puig-Valls 26 4 0 26 Oct 2023
Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability Haotian Xue Alexandre Araujo Bin Hu Yongxin Chen DiffM 136 48 0 25 May 2023
Policy Gradient Methods in the Presence of Symmetries and State Abstractions Prakash Panangaden S. Rezaei-Shoshtari Rosie Zhao David Meger Doina Precup 64 3 0 09 May 2023
Assessing Neural Network Robustness via Adversarial Pivotal Tuning Peter Ebert Christensen Vésteinn Snaebjarnarson Andrea Dittadi Serge Belongie Sagie Benaim AAML 74 1 0 17 Nov 2022
Combination of multiple neural networks using transfer learning and extensive geometric data augmentation for assessing cellularity scores in histopathology images Jacob Beckmann Kosta Popovic 49 0 0 09 Nov 2022
The Lie Derivative for Measuring Learned Equivariance Nate Gruver Marc Finzi Micah Goldblum A. Wilson 92 40 0 06 Oct 2022
A Closer Look at Robustness to L-infinity and Spatial Perturbations and their Composition Luke Rowe Benjamin Thérien Krzysztof Czarnecki Hongyang R. Zhang OOD 49 0 0 05 Oct 2022
Certified Robustness in Federated Learning Motasem Alfarra Juan C. Pérez Egor Shulgin Peter Richtárik Guohao Li AAML FedML 75 8 0 06 Jun 2022
CapsNet for Medical Image Segmentation Minh-Trieu Tran Viet-Khoa Vo-Ho Kyle Quinn Hien Nguyen Khoa Luu Ngan Le MedIm 52 5 0 16 Mar 2022
ReCasNet: Improving consistency within the two-stage mitosis detection framework Chawan Piansaddhayanon S. Santisukwongchote S. Shuangshoti Qingyi Tao S. Sriswasdi Ekapol Chuangsuwanich 29 10 0 28 Feb 2022
ML Attack Models: Adversarial Attacks and Data Poisoning Attacks Jing Lin Long Dang Mohamed Rahouti Kaiqi Xiong AAML 69 48 0 06 Dec 2021
Tightening the Approximation Error of Adversarial Risk with Auto Loss Function Search Pengfei Xia Ziqiang Li Bin Li AAML 112 3 0 09 Nov 2021
Adversarial Token Attacks on Vision Transformers Ameya Joshi Gauri Jagatap Chinmay Hegde ViT 99 19 0 08 Oct 2021
Anti-aliasing Deep Image Classifiers using Novel Depth Adaptive Blurring and Activation Function Md Tahmid Hossain S. Teng Ferdous Sohel Guojun Lu 76 13 0 03 Oct 2021
Unsolved Problems in ML Safety Dan Hendrycks Nicholas Carlini John Schulman Jacob Steinhardt 264 294 0 28 Sep 2021
Frequency Pooling: Shift-Equivalent and Anti-Aliasing Downsampling Zhendong Zhang OOD 29 5 0 24 Sep 2021
CC-Cert: A Probabilistic Approach to Certify General Robustness of Neural Networks Mikhail Aleksandrovich Pautov Nurislam Tursynbek Marina Munkhoeva Nikita Muravev Aleksandr Petiushko Ivan Oseledets AAML 84 16 0 22 Sep 2021
Capsule networks with non-iterative cluster routing Zhihao Zhao Samuel Cheng 24 10 0 19 Sep 2021
Robustness and Generalization via Generative Adversarial Training Omid Poursaeed Tianxing Jiang Harry Yang Serge Belongie SerNam Lim OOD AAML 68 26 0 06 Sep 2021
Imperceptible Adversarial Examples by Spatial Chroma-Shift A. Aydin Deniz Sen Berat Tuna Karli Oguz Hanoglu A. Temi̇zel AAML 49 16 0 05 Aug 2021
Improving Sound Event Classification by Increasing Shift Invariance in Convolutional Neural Networks Eduardo Fonseca Andrés Ferraro Xavier Serra AI4TS 121 9 0 01 Jul 2021
Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders M. Ziatdinov C. Wong Sergei V. Kalinin OOD 119 10 0 23 Jun 2021
Training or Architecture? How to Incorporate Invariance in Neural Networks Kanchana Vaishnavi Gandikota Jonas Geiping Zorah Lähner Adam Czapliñski Michael Moeller 3DPC OOD 61 10 0 18 Jun 2021
Localized Uncertainty Attacks Ousmane Amadou Dia Theofanis Karaletsos C. Hazirbas Cristian Canton Ferrer I. Kabul E. Meijer AAML 46 2 0 17 Jun 2021
Scale-invariant scale-channel networks: Deep networks that generalise to previously unseen scales Ylva Jansson T. Lindeberg 91 24 0 11 Jun 2021
Adversarial Attack Driven Data Augmentation for Accurate And Robust Medical Image Segmentation Mst. Tasnim Pervin Li Tao A. Huq Zuoxiang He Li Huo AAML OOD MedIm 67 10 0 25 May 2021
Probing the Effect of Selection Bias on Generalization: A Thought Experiment John K. Tsotsos Jun Luo CML 36 3 0 20 May 2021
Simple Transparent Adversarial Examples Jaydeep Borkar Pin-Yu Chen AAML 38 6 0 20 May 2021
Truly shift-equivariant convolutional neural networks with adaptive polyphase upsampling Anadi Chaman Ivan Dokmanić 67 9 0 09 May 2021
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety Sebastian Houben Stephanie Abrecht Maram Akila Andreas Bär Felix Brockherde ... Serin Varghese Michael Weber Sebastian J. Wirkert Tim Wirtz Matthias Woehrle AAML 121 58 0 29 Apr 2021
Fitting Elephants P. Mitra 18 0 0 31 Mar 2021
Generating Unrestricted Adversarial Examples via Three Parameters Hanieh Naderi Leili Goli S. Kasaei 83 9 0 13 Mar 2021
CovidGAN: Data Augmentation Using Auxiliary Classifier GAN for Improved Covid-19 Detection Abdul Waheed Muskan Goyal Deepak Gupta Ashish Khanna F. Al-turjman P. Pinheiro MedIm 92 581 0 08 Mar 2021
Tiny Adversarial Mulit-Objective Oneshot Neural Architecture Search Guoyang Xie Jinbao Wang Guo-Ding Yu Feng Zheng Yaochu Jin AAML 62 6 0 28 Feb 2021
Towards Robust Neural Networks via Close-loop Control Zhuotong Chen Qianxiao Li Zheng Zhang OOD AAML 79 25 0 03 Feb 2021
Exploring Adversarial Fake Images on Face Manifold Dongze Li Wei Wang Hongxing Fan Jing Dong AAML 88 44 0 09 Jan 2021
Understanding the Error in Evaluating Adversarial Robustness Pengfei Xia Ziqiang Li Hongjing Niu Bin Li AAML ELM 76 5 0 07 Jan 2021
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs Nikhil Kapoor C. Yuan Jonas Löhdefink Roland S. Zimmermann Serin Varghese Fabian Hüger Nico M. Schmidt Peter Schlicht Tim Fingscheidt AAML 39 4 0 02 Dec 2020
Deep Networks from the Principle of Rate Reduction Kwan Ho Ryan Chan Yaodong Yu Chong You Haozhi Qi John N. Wright Yi-An Ma 92 21 0 27 Oct 2020
Understanding Local Robustness of Deep Neural Networks under Natural Variations Ziyuan Zhong Yuchi Tian Baishakhi Ray AAML 51 1 0 09 Oct 2020
Block-wise Image Transformation with Secret Key for Adversarially Robust Defense Maungmaung Aprilpyone Hitoshi Kiya 73 57 0 02 Oct 2020
Bag of Tricks for Adversarial Training Tianyu Pang Xiao Yang Yinpeng Dong Hang Su Jun Zhu AAML 84 270 0 01 Oct 2020
Efficient Certification of Spatial Robustness Anian Ruoss Maximilian Baader Mislav Balunović Martin Vechev AAML 75 26 0 19 Sep 2020
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Yue Liu AAML 123 131 0 09 Sep 2020
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching Jonas Geiping Liam H. Fowl Wenjie Huang W. Czaja Gavin Taylor Michael Moeller Tom Goldstein AAML 100 222 0 04 Sep 2020
Perceptual Deep Neural Networks: Adversarial Robustness through Input Recreation Danilo Vasconcellos Vargas Bingli Liao Takahiro Kanzaki AAML 31 3 0 02 Sep 2020
Improving Resistance to Adversarial Deformations by Regularizing Gradients Pengfei Xia Bin Li AAML 43 4 0 29 Aug 2020
Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training Alfred Laugros A. Caplier Matthieu Ospici AAML 114 19 0 19 Aug 2020