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Approximating CNNs with Bag-of-local-Features models works surprisingly
  well on ImageNet

Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet

20 March 2019
Wieland Brendel
Matthias Bethge
    SSLFAtt
ArXiv (abs)PDFHTML

Papers citing "Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet"

50 / 312 papers shown
Title
InfoCons: Identifying Interpretable Critical Concepts in Point Clouds via Information Theory
InfoCons: Identifying Interpretable Critical Concepts in Point Clouds via Information Theory
Feifei Li
Mi Zhang
Zhaoxiang Wang
Min Yang
135
0
0
26 May 2025
Soft-CAM: Making black box models self-explainable for high-stakes decisions
K. Djoumessi
Philipp Berens
FAttBDL
233
0
0
23 May 2025
Interactivity x Explainability: Toward Understanding How Interactivity Can Improve Computer Vision Explanations
Interactivity x Explainability: Toward Understanding How Interactivity Can Improve Computer Vision Explanations
Indu Panigrahi
Sunnie S. Y. Kim
Amna Liaqat
Rohan Jinturkar
Olga Russakovsky
Ruth C. Fong
Parastoo Abtahi
FAttHAI
253
1
0
14 Apr 2025
A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Medical Image Classification
A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Medical Image Classification
K. Djoumessi
Samuel Ofosu Mensah
Philipp Berens
ViTMedIm
58
0
0
11 Apr 2025
v-CLR: View-Consistent Learning for Open-World Instance Segmentation
v-CLR: View-Consistent Learning for Open-World Instance Segmentation
Chang-Bin Zhang
Jinhong Ni
Yujie Zhong
Kai Han
3DVVLM
179
0
0
02 Apr 2025
Beyond Accuracy: What Matters in Designing Well-Behaved Models?
Beyond Accuracy: What Matters in Designing Well-Behaved Models?
Robin Hesse
Doğukan Bağcı
Bernt Schiele
Simone Schaub-Meyer
Stefan Roth
VLM
112
0
0
21 Mar 2025
Birds look like cars: Adversarial analysis of intrinsically interpretable deep learning
Hubert Baniecki
P. Biecek
AAML
122
0
0
11 Mar 2025
i-WiViG: Interpretable Window Vision GNN
Ivica Obadic
D. Kangin
Dario Augusto Borges Oliveira
Plamen Angelov
Xiao Xiang Zhu
131
0
0
11 Mar 2025
Disentangling Visual Transformers: Patch-level Interpretability for Image Classification
Disentangling Visual Transformers: Patch-level Interpretability for Image Classification
Guillaume Jeanneret
Loïc Simon
F. Jurie
ViT
158
0
0
24 Feb 2025
Unlearning-based Neural Interpretations
Unlearning-based Neural Interpretations
Ching Lam Choi
Alexandre Duplessis
Serge Belongie
FAtt
268
0
0
10 Oct 2024
InfoDisent: Explainability of Image Classification Models by Information Disentanglement
InfoDisent: Explainability of Image Classification Models by Information Disentanglement
Łukasz Struski
Dawid Rymarczyk
Jacek Tabor
120
1
0
16 Sep 2024
Say My Name: a Model's Bias Discovery Framework
Say My Name: a Model's Bias Discovery Framework
Massimiliano Ciranni
Luca Molinaro
C. Barbano
Attilio Fiandrotti
Vittorio Murino
Vito Paolo Pastore
Enzo Tartaglione
95
3
0
18 Aug 2024
Benchmarking the Attribution Quality of Vision Models
Benchmarking the Attribution Quality of Vision Models
Robin Hesse
Simone Schaub-Meyer
Stefan Roth
FAtt
91
3
0
16 Jul 2024
Knowledge distillation to effectively attain both region-of-interest and
  global semantics from an image where multiple objects appear
Knowledge distillation to effectively attain both region-of-interest and global semantics from an image where multiple objects appear
Seonwhee Jin
49
0
0
11 Jul 2024
This actually looks like that: Proto-BagNets for local and global
  interpretability-by-design
This actually looks like that: Proto-BagNets for local and global interpretability-by-design
K. Djoumessi
B. Bah
Laura Kühlewein
Philipp Berens
Lisa M. Koch
FAtt
75
2
0
21 Jun 2024
Real-Time Deepfake Detection in the Real-World
Real-Time Deepfake Detection in the Real-World
Bar Cavia
Eliahu Horwitz
Tal Reiss
Yedid Hoshen
119
8
0
13 Jun 2024
Attri-Net: A Globally and Locally Inherently Interpretable Model for
  Multi-Label Classification Using Class-Specific Counterfactuals
Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific Counterfactuals
Susu Sun
S. Woerner
Andreas Maier
Lisa M. Koch
Christian F. Baumgartner
FAtt
77
1
0
08 Jun 2024
How Video Meetings Change Your Expression
How Video Meetings Change Your Expression
Sumit Sarin
Utkarsh Mall
Purva Tendulkar
Carl Vondrick
CVBM
99
0
0
03 Jun 2024
Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial
  Training
Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training
Jiacheng Zhang
Feng Liu
Dawei Zhou
Jingfeng Zhang
Tongliang Liu
AAML
63
4
0
02 Jun 2024
Sharpness-Aware Minimization Enhances Feature Quality via Balanced
  Learning
Sharpness-Aware Minimization Enhances Feature Quality via Balanced Learning
Jacob Mitchell Springer
Vaishnavh Nagarajan
Aditi Raghunathan
120
6
0
30 May 2024
LucidPPN: Unambiguous Prototypical Parts Network for User-centric
  Interpretable Computer Vision
LucidPPN: Unambiguous Prototypical Parts Network for User-centric Interpretable Computer Vision
Mateusz Pach
Dawid Rymarczyk
K. Lewandowska
Jacek Tabor
Bartosz Zieliñski
80
8
0
23 May 2024
CICA: Content-Injected Contrastive Alignment for Zero-Shot Document
  Image Classification
CICA: Content-Injected Contrastive Alignment for Zero-Shot Document Image Classification
Sankalp Sinha
Muhammad Gul Zain Ali Khan
Talha Uddin Sheikh
Didier Stricker
Muhammad Zeshan Afzal
VLM
39
1
0
06 May 2024
ExMap: Leveraging Explainability Heatmaps for Unsupervised Group
  Robustness to Spurious Correlations
ExMap: Leveraging Explainability Heatmaps for Unsupervised Group Robustness to Spurious Correlations
Rwiddhi Chakraborty
Adrian Sletten
Michael C. Kampffmeyer
107
1
0
20 Mar 2024
Towards White Box Deep Learning
Towards White Box Deep Learning
Maciej Satkiewicz
AAML
88
1
0
14 Mar 2024
What Sketch Explainability Really Means for Downstream Tasks
What Sketch Explainability Really Means for Downstream Tasks
Hmrishav Bandyopadhyay
Pinaki Nath Chowdhury
A. Bhunia
Aneeshan Sain
Tao Xiang
Yi-Zhe Song
101
4
0
14 Mar 2024
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
77
5
0
17 Jan 2024
Seeing the roads through the trees: A benchmark for modeling spatial
  dependencies with aerial imagery
Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imagery
Caleb Robinson
Isaac Corley
Anthony Ortiz
Rahul Dodhia
J. L. Ferres
Peyman Najafirad
54
0
0
12 Jan 2024
TPatch: A Triggered Physical Adversarial Patch
TPatch: A Triggered Physical Adversarial Patch
Wenjun Zhu
Xiaoyu Ji
Yushi Cheng
Shibo Zhang
Wei Dong
AAML
108
27
0
30 Dec 2023
Foveation in the Era of Deep Learning
Foveation in the Era of Deep Learning
George Killick
Paul Henderson
Paul Siebert
Gerardo Aragon Camarasa
FedML
82
2
0
03 Dec 2023
Few-shot Shape Recognition by Learning Deep Shape-aware Features
Few-shot Shape Recognition by Learning Deep Shape-aware Features
Wenlong Shi
Changsheng Lu
Ming Shao
Yinjie Zhang
Si-Yu Xia
Piotr Koniusz
88
2
0
03 Dec 2023
Trustworthy Large Models in Vision: A Survey
Trustworthy Large Models in Vision: A Survey
Ziyan Guo
Li Xu
Jun Liu
MU
130
0
0
16 Nov 2023
Harnessing Synthetic Datasets: The Role of Shape Bias in Deep Neural
  Network Generalization
Harnessing Synthetic Datasets: The Role of Shape Bias in Deep Neural Network Generalization
Elior Benarous
Sotiris Anagnostidis
Luca Biggio
Thomas Hofmann
74
3
0
10 Nov 2023
Emergence of Shape Bias in Convolutional Neural Networks through
  Activation Sparsity
Emergence of Shape Bias in Convolutional Neural Networks through Activation Sparsity
Tianqin Li
Ziqi Wen
Yangfan Li
Tai Sing Lee
47
11
0
29 Oct 2023
A General Framework for Robust G-Invariance in G-Equivariant Networks
A General Framework for Robust G-Invariance in G-Equivariant Networks
Sophia Sanborn
Nina Miolane
AAMLOOD
84
4
0
28 Oct 2023
Detection Defenses: An Empty Promise against Adversarial Patch Attacks
  on Optical Flow
Detection Defenses: An Empty Promise against Adversarial Patch Attacks on Optical Flow
Erik Scheurer
Jenny Schmalfuss
Alexander Lis
Andrés Bruhn
AAML
76
6
0
26 Oct 2023
This Reads Like That: Deep Learning for Interpretable Natural Language
  Processing
This Reads Like That: Deep Learning for Interpretable Natural Language Processing
Claudio Fanconi
Moritz Vandenhirtz
Severin Husmann
Julia E. Vogt
FAtt
70
2
0
25 Oct 2023
PatchCURE: Improving Certifiable Robustness, Model Utility, and
  Computation Efficiency of Adversarial Patch Defenses
PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses
Chong Xiang
Tong Wu
Sihui Dai
Jonathan Petit
Suman Jana
Prateek Mittal
122
6
0
19 Oct 2023
SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models
SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models
Boyang Zhang
Zheng Li
Ziqing Yang
Xinlei He
Michael Backes
Mario Fritz
Yang Zhang
106
6
0
19 Oct 2023
Latent Diffusion Counterfactual Explanations
Latent Diffusion Counterfactual Explanations
Karim Farid
Simon Schrodi
Max Argus
Thomas Brox
DiffM
99
14
0
10 Oct 2023
DeViL: Decoding Vision features into Language
DeViL: Decoding Vision features into Language
Meghal Dani
Isabel Rio-Torto
Stephan Alaniz
Zeynep Akata
VLM
82
8
0
04 Sep 2023
FACET: Fairness in Computer Vision Evaluation Benchmark
FACET: Fairness in Computer Vision Evaluation Benchmark
Laura Gustafson
Chloe Rolland
Nikhila Ravi
Quentin Duval
Aaron B. Adcock
Cheng-Yang Fu
Melissa Hall
Candace Ross
VLMEGVM
117
40
0
31 Aug 2023
Video BagNet: short temporal receptive fields increase robustness in
  long-term action recognition
Video BagNet: short temporal receptive fields increase robustness in long-term action recognition
Ombretta Strafforello
X. Liu
Klamer Schutte
Jan van Gemert
42
2
0
22 Aug 2023
Foundation Model-oriented Robustness: Robust Image Model Evaluation with
  Pretrained Models
Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models
Peiyan Zhang
Hao Liu
Chaozhuo Li
Xing Xie
Sunghun Kim
Haohan Wang
VLMOOD
126
8
0
21 Aug 2023
ASPIRE: Language-Guided Data Augmentation for Improving Robustness
  Against Spurious Correlations
ASPIRE: Language-Guided Data Augmentation for Improving Robustness Against Spurious Correlations
Sreyan Ghosh
Chandra Kiran Reddy Evuru
Sonal Kumar
Utkarsh Tyagi
Sakshi Singh
Sanjoy Chowdhury
Dinesh Manocha
OOD
61
1
0
19 Aug 2023
Interpretability Benchmark for Evaluating Spatial Misalignment of
  Prototypical Parts Explanations
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations
Mikolaj Sacha
Bartosz Jura
Dawid Rymarczyk
Lukasz Struski
Jacek Tabor
Bartosz Zieliñski
70
14
0
16 Aug 2023
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of
  Explainable AI Methods
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods
Robin Hesse
Simone Schaub-Meyer
Stefan Roth
AAML
86
34
0
11 Aug 2023
A Majority Invariant Approach to Patch Robustness Certification for Deep
  Learning Models
A Majority Invariant Approach to Patch Robustness Certification for Deep Learning Models
Qili Zhou
Zhengyuan Wei
Haipeng Wang
William Chan
AAML
70
0
0
01 Aug 2023
The Co-12 Recipe for Evaluating Interpretable Part-Prototype Image
  Classifiers
The Co-12 Recipe for Evaluating Interpretable Part-Prototype Image Classifiers
Meike Nauta
Christin Seifert
99
12
0
26 Jul 2023
Right for the Wrong Reason: Can Interpretable ML Techniques Detect
  Spurious Correlations?
Right for the Wrong Reason: Can Interpretable ML Techniques Detect Spurious Correlations?
Susu Sun
Lisa M. Koch
Christian F. Baumgartner
94
16
0
23 Jul 2023
Complementary Frequency-Varying Awareness Network for Open-Set Fine-Grained Image Recognition
Complementary Frequency-Varying Awareness Network for Open-Set Fine-Grained Image Recognition
Qiulei Dong
Hong Wang
Qiulei Dong
104
0
0
14 Jul 2023
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