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1811.12231
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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
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Papers citing
"ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness"
50 / 453 papers shown
Title
Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU Models
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Limitations of Post-Hoc Feature Alignment for Robustness
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Detecting Spurious Correlations with Sanity Tests for Artificial Intelligence Guided Radiology Systems
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Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation
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Generative Adversarial Transformers
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Learning Transferable Visual Models From Natural Language Supervision
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On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness
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Improving Object Detection in Art Images Using Only Style Transfer
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Z. Bukhsh
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Counterfactual Generative Networks
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Andreas Geiger
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0
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Bridging In- and Out-of-distribution Samples for Their Better Discriminability
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25
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A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs
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27
4
0
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0
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Insights From A Large-Scale Database of Material Depictions In Paintings
Hubert Lin
Mitchell J. P. van Zuijlen
M. Wijntjes
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23
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Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander DÁmour
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This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition
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An analysis of the transfer learning of convolutional neural networks for artistic images
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Y. Gousseau
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14
18
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Learning Causal Semantic Representation for Out-of-Distribution Prediction
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46
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43
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29
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Permuted AdaIN: Reducing the Bias Towards Global Statistics in Image Classification
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Self-Supervised Variational Auto-Encoders
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30
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BOP Challenge 2020 on 6D Object Localization
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259
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15 Sep 2020
Adversarial score matching and improved sampling for image generation
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125
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11 Sep 2020
TRIER: Template-Guided Neural Networks for Robust and Interpretable Sleep Stage Identification from EEG Recordings
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32
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A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
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19
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What Should Not Be Contrastive in Contrastive Learning
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LSOTB-TIR:A Large-Scale High-Diversity Thermal Infrared Object Tracking Benchmark
Qiao Liu
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On Robustness and Transferability of Convolutional Neural Networks
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Jessica Yung
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D. Moldovan
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Do Adversarially Robust ImageNet Models Transfer Better?
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19
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Measuring Robustness to Natural Distribution Shifts in Image Classification
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0
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Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency
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116
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Conditional GAN for timeseries generation
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The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization
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High Resolution Zero-Shot Domain Adaptation of Synthetically Rendered Face Images
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Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation
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What shapes feature representations? Exploring datasets, architectures, and training
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Frustratingly Simple Domain Generalization via Image Stylization
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Emergent Properties of Foveated Perceptual Systems
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FenceMask: A Data Augmentation Approach for Pre-extracted Image Features
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A Lightweight CNN and Joint Shape-Joint Space (JS2) Descriptor for Radiological Osteoarthritis Detection
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6
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24 May 2020
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