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Learning with Noisy labels via Self-supervised Adversarial Noisy Masking

Learning with Noisy labels via Self-supervised Adversarial Noisy Masking

14 February 2023
Yuanpeng Tu
Boshen Zhang
Yuxi Li
Liang Liu
Jian Li
Jiangning Zhang
Yabiao Wang
Chengjie Wang
C. Zhao
    AAML
    NoLa
ArXivPDFHTML

Papers citing "Learning with Noisy labels via Self-supervised Adversarial Noisy Masking"

26 / 26 papers shown
Title
Selective-Supervised Contrastive Learning with Noisy Labels
Selective-Supervised Contrastive Learning with Noisy Labels
Shikun Li
Xiaobo Xia
Shiming Ge
Tongliang Liu
NoLa
63
176
0
08 Mar 2022
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
446
7,731
0
11 Nov 2021
Re-using Adversarial Mask Discriminators for Test-time Training under
  Distribution Shifts
Re-using Adversarial Mask Discriminators for Test-time Training under Distribution Shifts
Gabriele Valvano
Andrea Leo
Sotirios A. Tsaftaris
48
6
0
26 Aug 2021
Boosting Co-teaching with Compression Regularization for Label Noise
Boosting Co-teaching with Compression Regularization for Label Noise
Yingyi Chen
Xin Shen
S. Hu
Johan A. K. Suykens
NoLa
71
46
0
28 Apr 2021
Learning from Noisy Labels with Deep Neural Networks: A Survey
Learning from Noisy Labels with Deep Neural Networks: A Survey
Hwanjun Song
Minseok Kim
Dongmin Park
Yooju Shin
Jae-Gil Lee
NoLa
101
985
0
16 Jul 2020
Early-Learning Regularization Prevents Memorization of Noisy Labels
Early-Learning Regularization Prevents Memorization of Noisy Labels
Sheng Liu
Jonathan Niles-Weed
N. Razavian
C. Fernandez‐Granda
NoLa
99
565
0
30 Jun 2020
Combating noisy labels by agreement: A joint training method with
  co-regularization
Combating noisy labels by agreement: A joint training method with co-regularization
Hongxin Wei
Lei Feng
Xiangyu Chen
Bo An
NoLa
345
514
0
05 Mar 2020
DivideMix: Learning with Noisy Labels as Semi-supervised Learning
DivideMix: Learning with Noisy Labels as Semi-supervised Learning
Junnan Li
R. Socher
Guosheng Lin
NoLa
105
1,029
0
18 Feb 2020
Fine-grained Recognition: Accounting for Subtle Differences between
  Similar Classes
Fine-grained Recognition: Accounting for Subtle Differences between Similar Classes
Guolei Sun
Hisham Cholakkal
Salman Khan
Fahad Shahbaz Khan
Ling Shao
86
120
0
14 Dec 2019
Meta Label Correction for Noisy Label Learning
Meta Label Correction for Noisy Label Learning
Guoqing Zheng
Ahmed Hassan Awadallah
S. Dumais
NoLa
OffRL
101
182
0
10 Nov 2019
Deep Self-Learning From Noisy Labels
Deep Self-Learning From Noisy Labels
Jiangfan Han
Ping Luo
Xiaogang Wang
NoLa
58
280
0
06 Aug 2019
Understanding and Utilizing Deep Neural Networks Trained with Noisy
  Labels
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
Pengfei Chen
B. Liao
Guangyong Chen
Shengyu Zhang
NoLa
65
386
0
13 May 2019
Unsupervised Label Noise Modeling and Loss Correction
Unsupervised Label Noise Modeling and Loss Correction
Eric Arazo Sanchez
Diego Ortego
Paul Albert
Noel E. O'Connor
Kevin McGuinness
NoLa
78
611
0
25 Apr 2019
Probabilistic End-to-end Noise Correction for Learning with Noisy Labels
Probabilistic End-to-end Noise Correction for Learning with Noisy Labels
Kun Yi
Jianxin Wu
NoLa
66
417
0
19 Mar 2019
See Better Before Looking Closer: Weakly Supervised Data Augmentation
  Network for Fine-Grained Visual Classification
See Better Before Looking Closer: Weakly Supervised Data Augmentation Network for Fine-Grained Visual Classification
Tao Hu
H. Qi
Qingming Huang
Yan Lu
38
235
0
26 Jan 2019
How does Disagreement Help Generalization against Label Corruption?
How does Disagreement Help Generalization against Label Corruption?
Xingrui Yu
Bo Han
Jiangchao Yao
Gang Niu
Ivor W. Tsang
Masashi Sugiyama
NoLa
58
782
0
14 Jan 2019
Learning to Learn from Noisy Labeled Data
Learning to Learn from Noisy Labeled Data
Junnan Li
Yongkang Wong
Qi Zhao
Mohan Kankanhalli
NoLa
59
333
0
13 Dec 2018
Self-Erasing Network for Integral Object Attention
Self-Erasing Network for Integral Object Attention
Qibin Hou
Peng-Tao Jiang
Yunchao Wei
Ming-Ming Cheng
83
278
0
23 Oct 2018
Learning to Reweight Examples for Robust Deep Learning
Learning to Reweight Examples for Robust Deep Learning
Mengye Ren
Wenyuan Zeng
Binh Yang
R. Urtasun
OOD
NoLa
141
1,424
0
24 Mar 2018
Tell Me Where to Look: Guided Attention Inference Network
Tell Me Where to Look: Guided Attention Inference Network
Kunpeng Li
Ziyan Wu
Kuan-Chuan Peng
Jan Ernst
Y. Fu
106
531
0
27 Feb 2018
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
273
9,759
0
25 Oct 2017
A Closer Look at Memorization in Deep Networks
A Closer Look at Memorization in Deep Networks
Devansh Arpit
Stanislaw Jastrzebski
Nicolas Ballas
David M. Krueger
Emmanuel Bengio
...
Tegan Maharaj
Asja Fischer
Aaron Courville
Yoshua Bengio
Simon Lacoste-Julien
TDI
120
1,816
0
16 Jun 2017
Active Bias: Training More Accurate Neural Networks by Emphasizing High
  Variance Samples
Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples
Haw-Shiuan Chang
Erik Learned-Miller
Andrew McCallum
73
352
0
24 Apr 2017
Object Region Mining with Adversarial Erasing: A Simple Classification
  to Semantic Segmentation Approach
Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach
Yunchao Wei
Jiashi Feng
Xiaodan Liang
Ming-Ming Cheng
Yao-Min Zhao
Shuicheng Yan
75
808
0
24 Mar 2017
Learning Deep Features for Discriminative Localization
Learning Deep Features for Discriminative Localization
Bolei Zhou
A. Khosla
Àgata Lapedriza
A. Oliva
Antonio Torralba
SSL
SSeg
FAtt
250
9,308
0
14 Dec 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
271
19,045
0
20 Dec 2014
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