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ImageNet-trained CNNs are biased towards texture; increasing shape bias
  improves accuracy and robustness
v1v2v3 (latest)

ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

29 November 2018
Robert Geirhos
Patricia Rubisch
Claudio Michaelis
Matthias Bethge
Felix Wichmann
Wieland Brendel
ArXiv (abs)PDFHTML

Papers citing "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness"

50 / 1,489 papers shown
CrossNorm and SelfNorm for Generalization under Distribution Shifts
CrossNorm and SelfNorm for Generalization under Distribution ShiftsIEEE International Conference on Computer Vision (ICCV), 2021
Zhiqiang Tang
Yunhe Gao
Yi Zhu
Zhi-Li Zhang
Mu Li
Dimitris N. Metaxas
OOD
210
66
0
04 Feb 2021
Unbox the Black-box for the Medical Explainable AI via Multi-modal and
  Multi-centre Data Fusion: A Mini-Review, Two Showcases and Beyond
Unbox the Black-box for the Medical Explainable AI via Multi-modal and Multi-centre Data Fusion: A Mini-Review, Two Showcases and BeyondInformation Fusion (Inf. Fusion), 2021
Guang Yang
Qinghao Ye
Jun Xia
286
584
0
03 Feb 2021
Learning Graph Embeddings for Compositional Zero-shot Learning
Learning Graph Embeddings for Compositional Zero-shot LearningComputer Vision and Pattern Recognition (CVPR), 2021
Muhammad Ferjad Naeem
Yongqin Xian
Federico Tombari
Zeynep Akata
CoGe
307
181
0
03 Feb 2021
Learning domain-agnostic visual representation for computational
  pathology using medically-irrelevant style transfer augmentation
Learning domain-agnostic visual representation for computational pathology using medically-irrelevant style transfer augmentationIEEE Transactions on Medical Imaging (IEEE TMI), 2021
R. Yamashita
J. Long
Snikitha Banda
Jeanne Shen
D. Rubin
OODMedIm
171
61
0
02 Feb 2021
ConvNets for Counting: Object Detection of Transient Phenomena in
  Steelpan Drums
ConvNets for Counting: Object Detection of Transient Phenomena in Steelpan DrumsJournal of the Acoustical Society of America (JASA), 2021
Scott H. Hawley
Andrew C. Morrison
130
2
0
01 Feb 2021
Position, Padding and Predictions: A Deeper Look at Position Information
  in CNNs
Position, Padding and Predictions: A Deeper Look at Position Information in CNNsInternational Journal of Computer Vision (IJCV), 2021
Md. Amirul Islam
M. Kowal
Sen Jia
Konstantinos G. Derpanis
Neil D. B. Bruce
231
69
0
28 Jan 2021
Shape or Texture: Understanding Discriminative Features in CNNs
Shape or Texture: Understanding Discriminative Features in CNNsInternational Conference on Learning Representations (ICLR), 2021
Md. Amirul Islam
M. Kowal
Patrick Esser
Sen Jia
Bjorn Ommer
Konstantinos G. Derpanis
Neil D. B. Bruce
189
85
0
27 Jan 2021
DAF:re: A Challenging, Crowd-Sourced, Large-Scale, Long-Tailed Dataset
  For Anime Character Recognition
DAF:re: A Challenging, Crowd-Sourced, Large-Scale, Long-Tailed Dataset For Anime Character Recognition
Edwin Arkel Rios
Wen-Huang Cheng
Bo-Cheng Lai
CVBM
114
15
0
21 Jan 2021
Using Shape to Categorize: Low-Shot Learning with an Explicit Shape Bias
Using Shape to Categorize: Low-Shot Learning with an Explicit Shape BiasComputer Vision and Pattern Recognition (CVPR), 2021
Stefan Stojanov
Anh Thai
James M. Rehg
3DPC
228
85
0
18 Jan 2021
Machine learning with limited data
Machine learning with limited data
Fupin Yao
VLM
118
8
0
18 Jan 2021
What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space
What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space
Shihao Zhao
Jiabo He
Yisen Wang
James Bailey
Yue Liu
Yu-Gang Jiang
AAML
206
15
0
18 Jan 2021
Generating Attribution Maps with Disentangled Masked Backpropagation
Generating Attribution Maps with Disentangled Masked BackpropagationIEEE International Conference on Computer Vision (ICCV), 2021
Adria Ruiz
Antonio Agudo
Francesc Moreno
FAtt
174
3
0
17 Jan 2021
Removing Undesirable Feature Contributions Using Out-of-Distribution
  Data
Removing Undesirable Feature Contributions Using Out-of-Distribution DataInternational Conference on Learning Representations (ICLR), 2021
Saehyung Lee
Changhwa Park
Hyungyu Lee
Jihun Yi
Jonghyun Lee
Sungroh Yoon
OODD
323
26
0
17 Jan 2021
Robustness to Augmentations as a Generalization metric
Robustness to Augmentations as a Generalization metric
Sumukh K Aithal
D. Kashyap
Natarajan Subramanyam
OOD
76
19
0
16 Jan 2021
Counterfactual Generative Networks
Counterfactual Generative NetworksInternational Conference on Learning Representations (ICLR), 2021
Axel Sauer
Andreas Geiger
OODBDLCML
305
141
0
15 Jan 2021
CleftNet: Augmented Deep Learning for Synaptic Cleft Detection from
  Brain Electron Microscopy
CleftNet: Augmented Deep Learning for Synaptic Cleft Detection from Brain Electron MicroscopyIEEE Transactions on Medical Imaging (IEEE TMI), 2021
Lu Dong
Shuiwang Ji
119
15
0
12 Jan 2021
Bridging In- and Out-of-distribution Samples for Their Better
  Discriminability
Bridging In- and Out-of-distribution Samples for Their Better Discriminability
Engkarat Techapanurak
Anh-Chuong Dang
Takayuki Okatani
OODD
284
4
0
07 Jan 2021
Histogram Matching Augmentation for Domain Adaptation with Application
  to Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Image Segmentation
Histogram Matching Augmentation for Domain Adaptation with Application to Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Image Segmentation
Jun Ma
139
33
0
27 Dec 2020
Improving the Generalization of End-to-End Driving through Procedural
  Generation
Improving the Generalization of End-to-End Driving through Procedural Generation
Quanyi Li
Zhenghao Peng
Qihang Zhang
Chunxiao Liu
Bolei Zhou
289
19
0
26 Dec 2020
Revisiting Edge Detection in Convolutional Neural Networks
Revisiting Edge Detection in Convolutional Neural NetworksIEEE International Joint Conference on Neural Network (IJCNN), 2020
Minh Le
Subhradeep Kayal
FAtt
236
16
0
25 Dec 2020
Adversarial Momentum-Contrastive Pre-Training
Adversarial Momentum-Contrastive Pre-TrainingPattern Recognition Letters (PR), 2020
Cong Xu
Dan Li
Min Yang
SSL
323
16
0
24 Dec 2020
Unadversarial Examples: Designing Objects for Robust Vision
Unadversarial Examples: Designing Objects for Robust VisionNeural Information Processing Systems (NeurIPS), 2020
Hadi Salman
Andrew Ilyas
Logan Engstrom
Sai H. Vemprala
Aleksander Madry
Ashish Kapoor
WIGM
215
62
0
22 Dec 2020
Generative Interventions for Causal Learning
Generative Interventions for Causal LearningComputer Vision and Pattern Recognition (CVPR), 2020
Chengzhi Mao
Augustine Cha
Amogh Gupta
Hongya Wang
Junfeng Yang
Carl Vondrick
CMLOOD
267
70
0
22 Dec 2020
Image Translation via Fine-grained Knowledge Transfer
Image Translation via Fine-grained Knowledge Transfer
Xuanhong Chen
Ziang Liu
Ting Qiu
Bingbing Ni
Naiyuan Liu
Xiwei Hu
Yuhan Li
115
0
0
21 Dec 2020
Content Masked Loss: Human-Like Brush Stroke Planning in a Reinforcement
  Learning Painting Agent
Content Masked Loss: Human-Like Brush Stroke Planning in a Reinforcement Learning Painting AgentAAAI Conference on Artificial Intelligence (AAAI), 2020
Peter Schaldenbrand
Jean Oh
156
38
0
18 Dec 2020
Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild
  with Pose Annotations
Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose AnnotationsComputer Vision and Pattern Recognition (CVPR), 2020
Adel Ahmadyan
Liangkai Zhang
Jianing Wei
Artsiom Ablavatski
Matthias Grundmann
3DPC
719
206
0
18 Dec 2020
Fine-Grained Vehicle Perception via 3D Part-Guided Visual Data
  Augmentation
Fine-Grained Vehicle Perception via 3D Part-Guided Visual Data Augmentation
Feixiang Lu
Zongdai Liu
Huixin Miao
Peng Wang
Liangjun Zhang
Ruigang Yang
Tianyi Zhou
Bin Zhou
186
0
0
15 Dec 2020
Image Inpainting Guided by Coherence Priors of Semantics and Textures
Image Inpainting Guided by Coherence Priors of Semantics and TexturesComputer Vision and Pattern Recognition (CVPR), 2020
Liang Liao
Jing Xiao
Zechuan Wang
Chia-Wen Lin
Shiníchi Satoh
175
108
0
15 Dec 2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts
WILDS: A Benchmark of in-the-Wild Distribution ShiftsInternational Conference on Machine Learning (ICML), 2020
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
...
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Abigail Z. Jacobs
OOD
694
1,664
0
14 Dec 2020
Assessing The Importance Of Colours For CNNs In Object Recognition
Assessing The Importance Of Colours For CNNs In Object Recognition
Aditya Singh
Alessandro Bay
Andrea Mirabile
100
15
0
12 Dec 2020
Knowledge Capture and Replay for Continual Learning
Knowledge Capture and Replay for Continual LearningIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2020
Saisubramaniam Gopalakrishnan
Pranshu Ranjan Singh
Haytham M. Fayek
Savitha Ramasamy
Arulmurugan Ambikapathi
CLL
217
19
0
12 Dec 2020
Cyclic orthogonal convolutions for long-range integration of features
Cyclic orthogonal convolutions for long-range integration of features
Federica Freddi
Jezabel R. Garcia
Michael Bromberg
Sepehr Jalali
Da-shan Shiu
Alvin Chua
A. Bernacchia
136
0
0
11 Dec 2020
On the Binding Problem in Artificial Neural Networks
On the Binding Problem in Artificial Neural Networks
Klaus Greff
Sjoerd van Steenkiste
Jürgen Schmidhuber
OCL
582
290
0
09 Dec 2020
On 1/n neural representation and robustness
On 1/n neural representation and robustness
Josue Nassar
Piotr A. Sokól
SueYeon Chung
K. Harris
Il Memming Park
AAMLOOD
142
27
0
08 Dec 2020
Formatting the Landscape: Spatial conditional GAN for varying population
  in satellite imagery
Formatting the Landscape: Spatial conditional GAN for varying population in satellite imagery
T. Langer
N. Fedorova
R. Hagensieker
219
3
0
08 Dec 2020
A Singular Value Perspective on Model Robustness
A Singular Value Perspective on Model Robustness
Malhar Jere
Maghav Kumar
F. Koushanfar
AAML
231
7
0
07 Dec 2020
Materials In Paintings (MIP): An interdisciplinary dataset for
  perception, art history, and computer vision
Materials In Paintings (MIP): An interdisciplinary dataset for perception, art history, and computer visionPLoS ONE (PLOS ONE), 2020
Mitchell J. P. van Zuijlen
Hubert Lin
Kavita Bala
S. Pont
M. Wijntjes
212
15
0
05 Dec 2020
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined
  Augmentations Finetuning to Efficiently Improve the Robustness of CNNs
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNsComputer Science in Cars Symposium (CSC), 2020
Nikhil Kapoor
C. Yuan
Jonas Löhdefink
Roland S. Zimmermann
Serin Varghese
Fabian Hüger
Nico M. Schmidt
Peter Schlicht
Tim Fingscheidt
AAML
154
4
0
02 Dec 2020
Reducing Textural Bias Improves Robustness of Deep Segmentation Models
Reducing Textural Bias Improves Robustness of Deep Segmentation ModelsAnnual Conference on Medical Image Understanding and Analysis (MIUA), 2020
Seoin Chai
Daniel Rueckert
Ahmed E. Fetit
OOD
54
3
0
30 Nov 2020
Self-Supervised Real-to-Sim Scene Generation
Self-Supervised Real-to-Sim Scene GenerationIEEE International Conference on Computer Vision (ICCV), 2020
Aayush Prakash
Shoubhik Debnath
Jean-Francois Lafleche
Eric Cameracci
Gavriel State
Stan Birchfield
M. Law
202
29
0
30 Nov 2020
Improved Handling of Motion Blur in Online Object Detection
Improved Handling of Motion Blur in Online Object DetectionComputer Vision and Pattern Recognition (CVPR), 2020
Mohamed Sayed
Gabriel J. Brostow
AAML
192
30
0
29 Nov 2020
Differences between human and machine perception in medical diagnosis
Differences between human and machine perception in medical diagnosisScientific Reports (Sci Rep), 2020
Taro Makino
Stanislaw Jastrzebski
Witold Oleszkiewicz
Celin Chacko
Robin Ehrenpreis
...
D. Sodickson
Laura Heacock
Linda Moy
Dong Wang
Krzysztof J. Geras
AAML
175
31
0
28 Nov 2020
Squared $\ell_2$ Norm as Consistency Loss for Leveraging Augmented Data
  to Learn Robust and Invariant Representations
Squared ℓ2\ell_2ℓ2​ Norm as Consistency Loss for Leveraging Augmented Data to Learn Robust and Invariant Representations
Haohan Wang
Zeyi Huang
Xindi Wu
Eric Xing
160
2
0
25 Nov 2020
Insights From A Large-Scale Database of Material Depictions In Paintings
Insights From A Large-Scale Database of Material Depictions In Paintings
Hubert Lin
Mitchell J. P. van Zuijlen
M. Wijntjes
S. Pont
Kavita Bala
214
8
0
24 Nov 2020
Extreme Value Preserving Networks
Extreme Value Preserving Networks
Mingjie Sun
Jianguo Li
Changshui Zhang
AAMLMDE
126
0
0
17 Nov 2020
A Study of Domain Generalization on Ultrasound-based Multi-Class
  Segmentation of Arteries, Veins, Ligaments, and Nerves Using Transfer
  Learning
A Study of Domain Generalization on Ultrasound-based Multi-Class Segmentation of Arteries, Veins, Ligaments, and Nerves Using Transfer Learning
Edward Chen
T. Mathai
Vinit Sarode
Howie Choset
J. Galeotti
100
1
0
13 Nov 2020
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the
  Hessian
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the HessianNeural Information Processing Systems (NeurIPS), 2020
Jack Parker-Holder
Luke Metz
Cinjon Resnick
Hengyuan Hu
Adam Lerer
Alistair Letcher
A. Peysakhovich
Aldo Pacchiano
Jakob N. Foerster
188
25
0
12 Nov 2020
CheXphotogenic: Generalization of Deep Learning Models for Chest X-ray
  Interpretation to Photos of Chest X-rays
CheXphotogenic: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays
Pranav Rajpurkar
Anirudh Joshi
Anuj Pareek
Jeremy Irvin
A. Ng
M. Lungren
125
4
0
12 Nov 2020
Underspecification Presents Challenges for Credibility in Modern Machine
  Learning
Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander DÁmour
Katherine A. Heller
D. Moldovan
Ben Adlam
B. Alipanahi
...
Kellie Webster
Steve Yadlowsky
T. Yun
Xiaohua Zhai
D. Sculley
OffRL
448
766
0
06 Nov 2020
This Looks Like That, Because ... Explaining Prototypes for
  Interpretable Image Recognition
This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition
Meike Nauta
Annemarie Jutte
Jesper C. Provoost
C. Seifert
FAtt
335
74
0
05 Nov 2020
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