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Shape or Texture: Understanding Discriminative Features in CNNs

Shape or Texture: Understanding Discriminative Features in CNNs

27 January 2021
Md. Amirul Islam
M. Kowal
Patrick Esser
Sen Jia
Bjorn Ommer
Konstantinos G. Derpanis
Neil D. B. Bruce
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Papers citing "Shape or Texture: Understanding Discriminative Features in CNNs"

14 / 14 papers shown
Title
On the Relationship Between Double Descent of CNNs and Shape/Texture Bias Under Learning Process
Shun Iwase
Shuya Takahashi
Nakamasa Inoue
Rio Yokota
Ryo Nakamura
Hirokatsu Kataoka
77
0
0
04 Mar 2025
Trapped in texture bias? A large scale comparison of deep instance
  segmentation
Trapped in texture bias? A large scale comparison of deep instance segmentation
J. Theodoridis
Jessica Hofmann
J. Maucher
A. Schilling
SSeg
32
5
0
17 Jan 2024
Geometric Data Augmentations to Mitigate Distribution Shifts in Pollen
  Classification from Microscopic Images
Geometric Data Augmentations to Mitigate Distribution Shifts in Pollen Classification from Microscopic Images
Nam Cao
O. Saukh
29
2
0
18 Nov 2023
Texture Learning Domain Randomization for Domain Generalized
  Segmentation
Texture Learning Domain Randomization for Domain Generalized Segmentation
Sunghwan Kim
Dae-Hwan Kim
Hoseong Kim
19
18
0
21 Mar 2023
Prediction of Scene Plausibility
Prediction of Scene Plausibility
O. Nachmias
Ohad Fried
Ariel Shamir
3DV
34
0
0
02 Dec 2022
Unveiling the Tapestry: the Interplay of Generalization and Forgetting
  in Continual Learning
Unveiling the Tapestry: the Interplay of Generalization and Forgetting in Continual Learning
Zenglin Shi
Jing Jie
Ying Sun
J. Lim
Mengmi Zhang
CLL
39
1
0
21 Nov 2022
Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language
  Navigation
Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language Navigation
Peihao Chen
Dongyu Ji
Kun-Li Channing Lin
Runhao Zeng
Thomas H. Li
Mingkui Tan
Chuang Gan
SSL
36
62
0
14 Oct 2022
A Deeper Dive Into What Deep Spatiotemporal Networks Encode: Quantifying
  Static vs. Dynamic Information
A Deeper Dive Into What Deep Spatiotemporal Networks Encode: Quantifying Static vs. Dynamic Information
M. Kowal
Mennatullah Siam
Md. Amirul Islam
Neil D. B. Bruce
Richard P. Wildes
Konstantinos G. Derpanis
20
25
0
06 Jun 2022
Deep Digging into the Generalization of Self-Supervised Monocular Depth
  Estimation
Deep Digging into the Generalization of Self-Supervised Monocular Depth Estimation
Ji-Hoon Bae
Sungho Moon
Sunghoon Im
MDE
33
84
0
23 May 2022
Last Layer Re-Training is Sufficient for Robustness to Spurious
  Correlations
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
Polina Kirichenko
Pavel Izmailov
A. Wilson
OOD
49
318
0
06 Apr 2022
Robust Contrastive Learning Using Negative Samples with Diminished
  Semantics
Robust Contrastive Learning Using Negative Samples with Diminished Semantics
Songwei Ge
Shlok Kumar Mishra
Haohan Wang
Chun-Liang Li
David Jacobs
SSL
24
71
0
27 Oct 2021
Global Pooling, More than Meets the Eye: Position Information is Encoded
  Channel-Wise in CNNs
Global Pooling, More than Meets the Eye: Position Information is Encoded Channel-Wise in CNNs
Md. Amirul Islam
M. Kowal
Sen Jia
Konstantinos G. Derpanis
Neil D. B. Bruce
26
26
0
17 Aug 2021
Enhancing Self-supervised Video Representation Learning via Multi-level
  Feature Optimization
Enhancing Self-supervised Video Representation Learning via Multi-level Feature Optimization
Rui Qian
Yuxi Li
Huabin Liu
John See
Shuangrui Ding
Xian Liu
Dian Li
Weiyao Lin
35
42
0
04 Aug 2021
Intriguing Properties of Vision Transformers
Intriguing Properties of Vision Transformers
Muzammal Naseer
Kanchana Ranasinghe
Salman Khan
Munawar Hayat
Fahad Shahbaz Khan
Ming-Hsuan Yang
ViT
265
621
0
21 May 2021
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