A Survey on the Robustness of Computer Vision Models against Common Corruptions

10 May 2023

Shunxin Wang

Raymond N. J. Veldhuis

Papers citing "A Survey on the Robustness of Computer Vision Models against Common Corruptions"

50 / 102 papers shown

Title
Understanding Test-Time Augmentation Masanari Kimura ViT 48 30 0 10 Feb 2024
Domain Generalization with Vital Phase Augmentation Ingyun Lee Wooju Lee Hyun Myung OOD 26 3 0 27 Dec 2023
Robustmix: Improving Robustness by Regularizing the Frequency Bias of Deep Nets Jonas Ngnawé Marianne Abémgnigni Njifon Jonathan Heek Yann N. Dauphin OOD 34 5 0 06 Apr 2023
ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing Xiaodan Li YueFeng Chen Yao Zhu Shuhui Wang Rong Zhang Hui Xue 57 24 0 30 Mar 2023
A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking Chang-Shu Liu Yinpeng Dong Wenzhao Xiang Xiaohu Yang Hang Su Junyi Zhu YueFeng Chen Yuan He H. Xue Shibao Zheng OOD VLM AAML 72 79 0 28 Feb 2023
RLSbench: Domain Adaptation Under Relaxed Label Shift Saurabh Garg Nick Erickson James Sharpnack Alexander J. Smola Sivaraman Balakrishnan Zachary Chase Lipton VLM 65 32 0 06 Feb 2023
On Feature Learning in the Presence of Spurious Correlations Pavel Izmailov Polina Kirichenko Nate Gruver A. Wilson 91 128 0 20 Oct 2022
EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications Muhammad Maaz Abdelrahman M. Shaker Hisham Cholakkal Salman Khan Syed Waqas Zamir Rao Muhammad Anwer Fahad Shahbaz Khan ViT 86 198 0 21 Jun 2022
Can CNNs Be More Robust Than Transformers? Zeyu Wang Yutong Bai Yuyin Zhou Cihang Xie UQCV OOD 52 46 0 07 Jun 2022
A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities Yisheng Song Ting-Yuan Wang S. Mondal J. P. Sahoo SLR 110 369 0 13 May 2022
How Does Frequency Bias Affect the Robustness of Neural Image Classifiers against Common Corruption and Adversarial Perturbations? Alvin Chan Yew-Soon Ong Clement Tan AAML 43 13 0 09 May 2022
Understanding The Robustness in Vision Transformers Daquan Zhou Zhiding Yu Enze Xie Chaowei Xiao Anima Anandkumar Jiashi Feng J. Álvarez ViT 125 191 0 26 Apr 2022
MaxViT: Multi-Axis Vision Transformer Zhengzhong Tu Hossein Talebi Han Zhang Feng Yang P. Milanfar A. Bovik Yinxiao Li ViT 115 661 0 04 Apr 2022
ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches Maura Pintor Daniele Angioni Angelo Sotgiu Christian Scano Ambra Demontis Battista Biggio Fabio Roli AAML 72 52 0 07 Mar 2022
Fourier-Based Augmentations for Improved Robustness and Uncertainty Calibration Ryan Soklaski Michael Yee Theodoros Tsiligkaridis AAML 104 14 0 24 Feb 2022
NoisyMix: Boosting Model Robustness to Common Corruptions N. Benjamin Erichson Soon Hoe Lim Winnie Xu Francisco Utrera Ziang Cao Michael W. Mahoney 108 18 0 02 Feb 2022
A ConvNet for the 2020s Zhuang Liu Hanzi Mao Chaozheng Wu Christoph Feichtenhofer Trevor Darrell Saining Xie ViT 159 5,167 0 10 Jan 2022
PRIME: A few primitives can boost robustness to common corruptions Apostolos Modas Rahul Rade Guillermo Ortiz-Jiménez Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 51 44 0 27 Dec 2021
MViTv2: Improved Multiscale Vision Transformers for Classification and Detection Yanghao Li Chaoxia Wu Haoqi Fan K. Mangalam Bo Xiong Jitendra Malik Christoph Feichtenhofer ViT 144 689 0 02 Dec 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 45 53 0 29 Nov 2021
Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain Guangyao Chen Peixi Peng Li Ma Jia Li Lin Du Yonghong Tian AAML OOD 62 96 0 19 Aug 2021
From Show to Tell: A Survey on Deep Learning-based Image Captioning Matteo Stefanini Marcella Cornia Lorenzo Baraldi S. Cascianelli G. Fiameni Rita Cucchiara 3DV VLM MLLM 109 269 0 14 Jul 2021
VOLO: Vision Outlooker for Visual Recognition Li-xin Yuan Qibin Hou Zihang Jiang Jiashi Feng Shuicheng Yan ViT 104 327 0 24 Jun 2021
Can contrastive learning avoid shortcut solutions? Joshua Robinson Li Sun Ke Yu Kayhan Batmanghelich Stefanie Jegelka S. Sra SSL 69 144 0 21 Jun 2021
BEiT: BERT Pre-Training of Image Transformers Hangbo Bao Li Dong Songhao Piao Furu Wei ViT 258 2,824 0 15 Jun 2021
Knowledge distillation: A good teacher is patient and consistent Lucas Beyer Xiaohua Zhai Amelie Royer L. Markeeva Rohan Anil Alexander Kolesnikov VLM 107 295 0 09 Jun 2021
CoAtNet: Marrying Convolution and Attention for All Data Sizes Zihang Dai Hanxiao Liu Quoc V. Le Mingxing Tan ViT 109 1,204 0 09 Jun 2021
Vision Transformers are Robust Learners Sayak Paul Pin-Yu Chen ViT 59 311 0 17 May 2021
If your data distribution shifts, use self-learning E. Rusak Steffen Schneider George Pachitariu L. Eck Peter V. Gehler Oliver Bringmann Wieland Brendel Matthias Bethge VLM OOD TTA 113 32 0 27 Apr 2021
ImageNet-21K Pretraining for the Masses T. Ridnik Emanuel Ben-Baruch Asaf Noy Lihi Zelnik-Manor SSeg VLM CLIP 284 701 0 22 Apr 2021
LiBRe: A Practical Bayesian Approach to Adversarial Detection Zhijie Deng Xiao Yang Shizhen Xu Hang Su Jun Zhu BDL AAML 42 62 0 27 Mar 2021
Understanding Robustness of Transformers for Image Classification Srinadh Bhojanapalli Ayan Chakrabarti Daniel Glasner Daliang Li Thomas Unterthiner Andreas Veit ViT 85 385 0 26 Mar 2021
Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU Models Mengnan Du Varun Manjunatha R. Jain Ruchi Deshpande Franck Dernoncourt Jiuxiang Gu Tong Sun Xia Hu 85 108 0 11 Mar 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts Pang Wei Koh Shiori Sagawa Henrik Marklund Sang Michael Xie Marvin Zhang ... A. Kundaje Emma Pierson Sergey Levine Chelsea Finn Percy Liang OOD 172 1,428 0 14 Dec 2020
A Survey on Deep Learning with Noisy Labels: How to train your model when you cannot trust on the annotations? F. Cordeiro G. Carneiro NoLa 100 48 0 05 Dec 2020
A Decade Survey of Content Based Image Retrieval using Deep Learning S. Dubey VLM BDL 56 219 0 23 Nov 2020
Better Aggregation in Test-Time Augmentation Divya Shanmugam Davis W. Blalock Guha Balakrishnan John Guttag ViT 58 148 0 23 Nov 2020
Gradient Starvation: A Learning Proclivity in Neural Networks Mohammad Pezeshki Sekouba Kaba Yoshua Bengio Aaron Courville Doina Precup Guillaume Lajoie MLT 116 266 0 18 Nov 2020
A Survey of Label-noise Representation Learning: Past, Present and Future Bo Han Quanming Yao Tongliang Liu Gang Niu Ivor W. Tsang James T. Kwok Masashi Sugiyama NoLa 43 162 0 09 Nov 2020
Robust Pre-Training by Adversarial Contrastive Learning Ziyu Jiang Tianlong Chen Ting-Li Chen Zhangyang Wang 96 232 0 26 Oct 2020
Learning Loss for Test-Time Augmentation Ildoo Kim Younghoon Kim Sungwoong Kim OOD 57 92 0 22 Oct 2020
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness Long Zhao Ting Liu Xi Peng Dimitris N. Metaxas OOD AAML 97 168 0 15 Oct 2020
Respecting Domain Relations: Hypothesis Invariance for Domain Generalization Ziqi Wang Marco Loog Jan van Gemert OOD 49 48 0 15 Oct 2020
Sharpness-Aware Minimization for Efficiently Improving Generalization Pierre Foret Ariel Kleiner H. Mobahi Behnam Neyshabur AAML 184 1,349 0 03 Oct 2020
Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup Jang-Hyun Kim Wonho Choo Hyun Oh Song AAML 83 390 0 15 Sep 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey Hwanjun Song Minseok Kim Dongmin Park Yooju Shin Jae-Gil Lee NoLa 101 985 0 16 Jul 2020
Measuring Robustness to Natural Distribution Shifts in Image Classification Rohan Taori Achal Dave Vaishaal Shankar Nicholas Carlini Benjamin Recht Ludwig Schmidt OOD 108 546 0 01 Jul 2020
Improving robustness against common corruptions by covariate shift adaptation Steffen Schneider E. Rusak L. Eck Oliver Bringmann Wieland Brendel Matthias Bethge VLM 92 480 0 30 Jun 2020
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization Dan Hendrycks Steven Basart Norman Mu Saurav Kadavath Frank Wang ... Samyak Parajuli Mike Guo D. Song Jacob Steinhardt Justin Gilmer OOD 328 1,734 0 29 Jun 2020
The Pitfalls of Simplicity Bias in Neural Networks Harshay Shah Kaustav Tamuly Aditi Raghunathan Prateek Jain Praneeth Netrapalli AAML 65 359 0 13 Jun 2020