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Empirically Analyzing the Effect of Dataset Biases on Deep Face
  Recognition Systems

Empirically Analyzing the Effect of Dataset Biases on Deep Face Recognition Systems

5 December 2017
Adam Kortylewski
Bernhard Egger
Andreas C. Schneider
Thomas Gerig
Andreas Morel-Forster
T. Vetter
    CVBM
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Papers citing "Empirically Analyzing the Effect of Dataset Biases on Deep Face Recognition Systems"

17 / 17 papers shown
Title
A Bayesian Approach to OOD Robustness in Image Classification
A Bayesian Approach to OOD Robustness in Image Classification
Prakhar Kaushik
Adam Kortylewski
Alan Yuille
26
1
0
12 Mar 2024
AI-Generated Images as Data Source: The Dawn of Synthetic Era
AI-Generated Images as Data Source: The Dawn of Synthetic Era
Zuhao Yang
Fangneng Zhan
Kunhao Liu
Muyu Xu
Shijian Lu
EGVM
31
18
0
03 Oct 2023
PoseExaminer: Automated Testing of Out-of-Distribution Robustness in
  Human Pose and Shape Estimation
PoseExaminer: Automated Testing of Out-of-Distribution Robustness in Human Pose and Shape Estimation
Qihao Liu
Adam Kortylewski
Alan Yuille
OODD
46
12
0
13 Mar 2023
Linking convolutional kernel size to generalization bias in face
  analysis CNNs
Linking convolutional kernel size to generalization bias in face analysis CNNs
Hao Liang
J. O. Caro
Vikram Maheshri
Ankit B. Patel
Guha Balakrishnan
CVBM
CML
23
0
0
07 Feb 2023
Finding Differences Between Transformers and ConvNets Using
  Counterfactual Simulation Testing
Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing
Nataniel Ruiz
Sarah Adel Bargal
Cihang Xie
Kate Saenko
Stan Sclaroff
ViT
39
5
0
29 Nov 2022
The Impact of Racial Distribution in Training Data on Face Recognition
  Bias: A Closer Look
The Impact of Racial Distribution in Training Data on Face Recognition Bias: A Closer Look
Manideep Kolla
Aravinth Savadamuthu
CVBM
32
11
0
26 Nov 2022
Human Body Measurement Estimation with Adversarial Augmentation
Human Body Measurement Estimation with Adversarial Augmentation
Nataniel Ruiz
Míriam Bellver
Timo Bolkart
Ambuj Arora
Ming-Chia Lin
Javier Romero
Raj Bala
3DH
39
3
0
11 Oct 2022
Causality-Inspired Taxonomy for Explainable Artificial Intelligence
Causality-Inspired Taxonomy for Explainable Artificial Intelligence
Pedro C. Neto
Tiago B. Gonccalves
João Ribeiro Pinto
W. Silva
Ana F. Sequeira
Arun Ross
Jaime S. Cardoso
XAI
43
12
0
19 Aug 2022
Synthetic Data in Human Analysis: A Survey
Synthetic Data in Human Analysis: A Survey
Indu Joshi
Marcel Grimmer
Christian Rathgeb
Christoph Busch
F. Brémond
A. Dantcheva
40
46
0
19 Aug 2022
Towards Inclusive HRI: Using Sim2Real to Address Underrepresentation in
  Emotion Expression Recognition
Towards Inclusive HRI: Using Sim2Real to Address Underrepresentation in Emotion Expression Recognition
Saba Akhyani
Mehryar Abbasi Boroujeni
Mo Chen
Angelica Lim
44
4
0
15 Aug 2022
SCAMPS: Synthetics for Camera Measurement of Physiological Signals
SCAMPS: Synthetics for Camera Measurement of Physiological Signals
Daniel J. McDuff
Miah Wander
Xin Liu
B. Hill
Javier Hernández
Jonathan Lester
T. Baltrušaitis
37
39
0
08 Jun 2022
OOD-CV: A Benchmark for Robustness to Out-of-Distribution Shifts of
  Individual Nuisances in Natural Images
OOD-CV: A Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images
Bingchen Zhao
Shaozuo Yu
Wufei Ma
M. Yu
Shenxiao Mei
Angtian Wang
Ju He
Alan Yuille
Adam Kortylewski
31
53
0
29 Nov 2021
Discover the Unknown Biased Attribute of an Image Classifier
Discover the Unknown Biased Attribute of an Image Classifier
Zhiheng Li
Chenliang Xu
30
50
0
29 Apr 2021
Synthetic Humans for Action Recognition from Unseen Viewpoints
Synthetic Humans for Action Recognition from Unseen Viewpoints
Gül Varol
Ivan Laptev
Cordelia Schmid
Andrew Zisserman
33
96
0
09 Dec 2019
Synthetic Data for Deep Learning
Synthetic Data for Deep Learning
Sergey I. Nikolenko
46
348
0
25 Sep 2019
Characterizing Bias in Classifiers using Generative Models
Characterizing Bias in Classifiers using Generative Models
Daniel J. McDuff
Shuang Ma
Yale Song
Ashish Kapoor
31
47
0
30 May 2019
Training Deep Face Recognition Systems with Synthetic Data
Training Deep Face Recognition Systems with Synthetic Data
Adam Kortylewski
Andreas C. Schneider
Thomas Gerig
Bernhard Egger
Andreas Morel-Forster
T. Vetter
42
48
0
16 Feb 2018
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