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ContraCluster: Learning to Classify without Labels by Contrastive
  Self-Supervision and Prototype-Based Semi-Supervision

ContraCluster: Learning to Classify without Labels by Contrastive Self-Supervision and Prototype-Based Semi-Supervision

19 April 2023
Seongho Joe
Byoungjip Kim
Ho. Kang
Kyoungwon Park
Bogun Kim
Jaeseon Park
Joonseok Lee
Youngjune Gwon
    SSL
ArXivPDFHTML

Papers citing "ContraCluster: Learning to Classify without Labels by Contrastive Self-Supervision and Prototype-Based Semi-Supervision"

4 / 4 papers shown
Title
Bridging the Gaps: Utilizing Unlabeled Face Recognition Datasets to
  Boost Semi-Supervised Facial Expression Recognition
Bridging the Gaps: Utilizing Unlabeled Face Recognition Datasets to Boost Semi-Supervised Facial Expression Recognition
Jie Song
Mengqiao He
Jinhua Feng
B. S.
22
0
0
23 Oct 2024
SelfMatch: Combining Contrastive Self-Supervision and Consistency for
  Semi-Supervised Learning
SelfMatch: Combining Contrastive Self-Supervision and Consistency for Semi-Supervised Learning
Byoungjip Kim
Jinho Choo
Yeong-Dae Kwon
Seongho Joe
Seungjai Min
Youngjune Gwon
SSL
21
52
0
16 Jan 2021
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks
Hieu H. Pham
Quoc V. Le
63
56
0
05 Jan 2021
Mean teachers are better role models: Weight-averaged consistency
  targets improve semi-supervised deep learning results
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen
Harri Valpola
OOD
MoMe
244
1,275
0
06 Mar 2017
1