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CoDiM: Learning with Noisy Labels via Contrastive Semi-Supervised
  Learning

CoDiM: Learning with Noisy Labels via Contrastive Semi-Supervised Learning

23 November 2021
Xin Zhang
Zixuan Liu
Kaiwen Xiao
Tian Shen
Junzhou Huang
Wei Yang
Dimitris Samaras
Xiao Han
    NoLa
ArXivPDFHTML

Papers citing "CoDiM: Learning with Noisy Labels via Contrastive Semi-Supervised Learning"

3 / 3 papers shown
Title
Sample Selection via Contrastive Fragmentation for Noisy Label Regression
Sample Selection via Contrastive Fragmentation for Noisy Label Regression
C. Kim
Sangwoo Moon
Jihwan Moon
Dongyeon Woo
Gunhee Kim
NoLa
52
0
0
25 Feb 2025
Is one annotation enough? A data-centric image classification benchmark
  for noisy and ambiguous label estimation
Is one annotation enough? A data-centric image classification benchmark for noisy and ambiguous label estimation
Lars Schmarje
Vasco Grossmann
Claudius Zelenka
S. Dippel
R. Kiko
...
M. Pastell
J. Stracke
A. Valros
N. Volkmann
Reinahrd Koch
33
34
0
13 Jul 2022
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
240
3,367
0
09 Mar 2020
1