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Built-in Elastic Transformations for Improved Robustness

Built-in Elastic Transformations for Improved Robustness

20 July 2021
Sadaf Gulshad
Ivan Sosnovik
A. Smeulders
    AAML
ArXivPDFHTML

Papers citing "Built-in Elastic Transformations for Improved Robustness"

22 / 22 papers shown
Title
Natural Perturbed Training for General Robustness of Neural Network
  Classifiers
Natural Perturbed Training for General Robustness of Neural Network Classifiers
Sadaf Gulshad
A. Smeulders
OOD
AAML
29
2
0
21 Mar 2021
Revisiting Batch Normalization for Improving Corruption Robustness
Revisiting Batch Normalization for Improving Corruption Robustness
Philipp Benz
Chaoning Zhang
Adil Karjauv
In So Kweon
36
83
0
07 Oct 2020
Scale Equivariance Improves Siamese Tracking
Scale Equivariance Improves Siamese Tracking
Ivan Sosnovik
A. Moskalev
A. Smeulders
48
79
0
17 Jul 2020
Learning perturbation sets for robust machine learning
Learning perturbation sets for robust machine learning
Eric Wong
J. Zico Kolter
OOD
51
81
0
16 Jul 2020
Improving robustness against common corruptions by covariate shift
  adaptation
Improving robustness against common corruptions by covariate shift adaptation
Steffen Schneider
E. Rusak
L. Eck
Oliver Bringmann
Wieland Brendel
Matthias Bethge
VLM
90
480
0
30 Jun 2020
Model-Based Robust Deep Learning: Generalizing to Natural,
  Out-of-Distribution Data
Model-Based Robust Deep Learning: Generalizing to Natural, Out-of-Distribution Data
Alexander Robey
Hamed Hassani
George J. Pappas
OOD
78
43
0
20 May 2020
Scale-Equivariant Steerable Networks
Scale-Equivariant Steerable Networks
Li Xiao
Michal Szmaja
A. Smeulders
115
149
0
14 Oct 2019
Adversarial Neural Pruning with Latent Vulnerability Suppression
Adversarial Neural Pruning with Latent Vulnerability Suppression
Divyam Madaan
Jinwoo Shin
Sung Ju Hwang
AAML
16
3
0
12 Aug 2019
Interpreting Adversarially Trained Convolutional Neural Networks
Interpreting Adversarially Trained Convolutional Neural Networks
Tianyuan Zhang
Zhanxing Zhu
AAML
GAN
FAtt
88
161
0
23 May 2019
Theoretically Principled Trade-off between Robustness and Accuracy
Theoretically Principled Trade-off between Robustness and Accuracy
Hongyang R. Zhang
Yaodong Yu
Jiantao Jiao
Eric Xing
L. Ghaoui
Michael I. Jordan
129
2,548
0
24 Jan 2019
Albumentations: fast and flexible image augmentations
Albumentations: fast and flexible image augmentations
A. Buslaev
Alex Parinov
Eugene Khvedchenya
V. Iglovikov
Alexandr A Kalinin
136
1,973
0
18 Sep 2018
Do CIFAR-10 Classifiers Generalize to CIFAR-10?
Do CIFAR-10 Classifiers Generalize to CIFAR-10?
Benjamin Recht
Rebecca Roelofs
Ludwig Schmidt
Vaishaal Shankar
OOD
FedML
ELM
164
409
0
01 Jun 2018
Why do deep convolutional networks generalize so poorly to small image
  transformations?
Why do deep convolutional networks generalize so poorly to small image transformations?
Aharon Azulay
Yair Weiss
68
560
0
30 May 2018
Robustness May Be at Odds with Accuracy
Robustness May Be at Odds with Accuracy
Dimitris Tsipras
Shibani Santurkar
Logan Engstrom
Alexander Turner
Aleksander Madry
AAML
93
1,778
0
30 May 2018
Provable defenses against adversarial examples via the convex outer
  adversarial polytope
Provable defenses against adversarial examples via the convex outer adversarial polytope
Eric Wong
J. Zico Kolter
AAML
110
1,501
0
02 Nov 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
285
12,060
0
19 Jun 2017
A Study and Comparison of Human and Deep Learning Recognition
  Performance Under Visual Distortions
A Study and Comparison of Human and Deep Learning Recognition Performance Under Visual Distortions
Samuel F. Dodge
Lina Karam
3DH
57
421
0
06 May 2017
Deformable Convolutional Networks
Deformable Convolutional Networks
Jifeng Dai
Haozhi Qi
Yuwen Xiong
Yi Li
Guodong Zhang
Han Hu
Yichen Wei
196
5,330
0
17 Mar 2017
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
328
7,980
0
23 May 2016
Structured Receptive Fields in CNNs
Structured Receptive Fields in CNNs
J. Jacobsen
Jan van Gemert
Zhongyu Lou
A. Smeulders
58
107
0
10 May 2016
Spatial Transformer Networks
Spatial Transformer Networks
Max Jaderberg
Karen Simonyan
Andrew Zisserman
Koray Kavukcuoglu
292
7,383
0
05 Jun 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
252
19,045
0
20 Dec 2014
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