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Towards Semi-Supervised Deep Facial Expression Recognition with An
  Adaptive Confidence Margin

Towards Semi-Supervised Deep Facial Expression Recognition with An Adaptive Confidence Margin

23 March 2022
Hangyu Li
N. Wang
Xi Yang
Xiaoyu Wang
Xinbo Gao
    CVBM
ArXivPDFHTML

Papers citing "Towards Semi-Supervised Deep Facial Expression Recognition with An Adaptive Confidence Margin"

5 / 5 papers shown
Title
Adaptive Margin Contrastive Learning for Ambiguity-aware 3D Semantic Segmentation
Adaptive Margin Contrastive Learning for Ambiguity-aware 3D Semantic Segmentation
Yang Chen
Yueqi Duan
Runzhong Zhang
Yap-Peng Tan
3DPC
136
2
0
06 Feb 2025
Towards Semi-supervised Universal Graph Classification
Towards Semi-supervised Universal Graph Classification
Xiao Luo
Yusheng Zhao
Yifang Qin
Wei Ju
Ming Zhang
15
30
0
31 May 2023
Rethinking the Learning Paradigm for Facial Expression Recognition
Rethinking the Learning Paradigm for Facial Expression Recognition
Weijie Wang
N. Sebe
Bruno Lepri
29
2
0
30 Sep 2022
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo
  Labeling
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling
Bowen Zhang
Yidong Wang
Wenxin Hou
Hao Wu
Jindong Wang
Manabu Okumura
T. Shinozaki
AAML
218
862
0
15 Oct 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