Revisiting Batch Normalization for Improving Corruption Robustness

7 October 2020

In So Kweon

Papers citing "Revisiting Batch Normalization for Improving Corruption Robustness"

24 / 24 papers shown

Title
On-demand Test-time Adaptation for Edge Devices Xiao Ma Young D. Kwon Dong-Lai Ma TTA 55 0 0 02 May 2025
Test-time Adaptation for Regression by Subspace Alignment Kazuki Adachi Shin'ya Yamaguchi Atsutoshi Kumagai Tomoki Hamagami TTA 46 0 0 04 Oct 2024
Improving robustness to corruptions with multiplicative weight perturbations Trung Trinh Markus Heinonen Luigi Acerbi Samuel Kaski 44 0 0 24 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 39 3 0 29 Mar 2024
Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation Devavrat Tomar Guillaume Vray Jean-Philippe Thiran Behzad Bozorgtabar 43 3 0 16 Jan 2024
REALM: Robust Entropy Adaptive Loss Minimization for Improved Single-Sample Test-Time Adaptation Skyler Seto B. Theobald Federico Danieli Navdeep Jaitly Dan Busbridge TTA OOD 45 6 0 07 Sep 2023
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods A. Ma Yangchen Pan Amir-massoud Farahmand AAML 25 5 0 13 Aug 2023
On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis Divyam Madaan D. Sodickson K. Cho S. Chopra OOD MedIm 30 1 0 23 Jun 2023
Understanding the Robustness of Multi-Exit Models under Common Corruptions Akshay Mehra Skyler Seto Navdeep Jaitly B. Theobald AAML 16 3 0 03 Dec 2022
Benchmarking performance of object detection under image distortions in an uncontrolled environment Ayman Beghdadi Malik Mallem Lotfi Beji 36 5 0 28 Oct 2022
Learning Less Generalizable Patterns with an Asymmetrically Trained Double Classifier for Better Test-Time Adaptation Thomas Duboudin Emmanuel Dellandrea Corentin Abgrall Gilles Hénaff Limin Chen TTA 27 1 0 17 Oct 2022
Removing Batch Normalization Boosts Adversarial Training Haotao Wang Aston Zhang Shuai Zheng Xingjian Shi Mu Li Zhangyang Wang 40 41 0 04 Jul 2022
Test-time Batch Normalization Tao Yang Shenglong Zhou Yuwang Wang Yan Lu Nanning Zheng OOD 57 9 0 20 May 2022
Uncertainty Modeling for Out-of-Distribution Generalization Xiaotong Li Yongxing Dai Yixiao Ge Jun Liu Ying Shan Ling-Yu Duan OODD OOD 34 175 0 08 Feb 2022
Improving Robustness by Enhancing Weak Subnets Yong Guo David Stutz Bernt Schiele AAML 27 15 0 30 Jan 2022
Wiggling Weights to Improve the Robustness of Classifiers Sadaf Gulshad Ivan Sosnovik A. Smeulders OOD 28 0 0 18 Nov 2021
Anti-aliasing Deep Image Classifiers using Novel Depth Adaptive Blurring and Activation Function Md Tahmid Hossain S. Teng Ferdous Sohel Guojun Lu 49 13 0 03 Oct 2021
Built-in Elastic Transformations for Improved Robustness Sadaf Gulshad Ivan Sosnovik A. Smeulders AAML 22 1 0 20 Jul 2021
Test-Time Adaptation to Distribution Shift by Confidence Maximization and Input Transformation Chaithanya Kumar Mummadi Robin Hutmacher K. Rambach Evgeny Levinkov Thomas Brox J. H. Metzen TTA OOD 35 70 0 28 Jun 2021
Universal Adversarial Training with Class-Wise Perturbations Philipp Benz Chaoning Zhang Adil Karjauv In So Kweon AAML 22 26 0 07 Apr 2021
The Devil is in the Boundary: Exploiting Boundary Representation for Basis-based Instance Segmentation Myungchul Kim Sanghyun Woo Dahun Kim In So Kweon ISeg 19 20 0 26 Nov 2020
Robustness May Be at Odds with Fairness: An Empirical Study on Class-wise Accuracy Philipp Benz Chaoning Zhang Adil Karjauv In So Kweon AAML 24 57 0 26 Oct 2020
Robust Image Classification Using A Low-Pass Activation Function and DCT Augmentation Md Tahmid Hossain S. Teng Ferdous Sohel Guojun Lu 16 10 0 18 Jul 2020
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 297 10,225 0 16 Nov 2016