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2211.01866
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ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations
3 November 2022
Badr Youbi Idrissi
Diane Bouchacourt
Randall Balestriero
Ivan Evtimov
C. Hazirbas
Nicolas Ballas
Pascal Vincent
M. Drozdzal
David Lopez-Paz
Mark Ibrahim
VLM
ViT
Re-assign community
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Papers citing
"ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations"
6 / 6 papers shown
Title
Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers
Quentin Guimard
Moreno DÍncà
Massimiliano Mancini
Elisa Ricci
SSL
72
0
0
29 Apr 2025
Provably Safeguarding a Classifier from OOD and Adversarial Samples: an Extreme Value Theory Approach
Nicolas Atienza
Christophe Labreuche
Johanne Cohen
Michele Sebag
OODD
AAML
84
0
0
20 Jan 2025
Cross-Entropy Is All You Need To Invert the Data Generating Process
Patrik Reizinger
Alice Bizeul
Attila Juhos
Julia E. Vogt
Randall Balestriero
Wieland Brendel
David Klindt
SSL
OOD
BDL
DRL
73
3
0
29 Oct 2024
Are Deep Neural Networks Adequate Behavioural Models of Human Visual Perception?
Felix Wichmann
Robert Geirhos
25
25
0
26 May 2023
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels
Sangdoo Yun
Seong Joon Oh
Byeongho Heo
Dongyoon Han
Junsuk Choe
Sanghyuk Chun
384
142
0
13 Jan 2021
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
282
39,170
0
01 Sep 2014
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