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Open-Set Facial Expression Recognition

Open-Set Facial Expression Recognition

23 January 2024
Yuhang Zhang
Yue Yao
Xuannan Liu
Lixiong Qin
Wenjing Wang
Weihong Deng
    CVBM
ArXiv (abs)PDFHTML

Papers citing "Open-Set Facial Expression Recognition"

15 / 15 papers shown
Title
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
Yezhen Wang
Yue Liu
Tong Che
Kaiyang Zhou
Ziwei Liu
Dongsheng Li
UQCV
64
51
0
27 Jul 2021
Feature Decomposition and Reconstruction Learning for Effective Facial
  Expression Recognition
Feature Decomposition and Reconstruction Learning for Effective Facial Expression Recognition
Delian Ruan
Yan Yan
Shenqi Lai
Z. Chai
Chunhua Shen
Hanzi Wang
CVBM
77
133
0
12 Apr 2021
Learning Placeholders for Open-Set Recognition
Learning Placeholders for Open-Set Recognition
Da-Wei Zhou
Han-Jia Ye
De-Chuan Zhan
VLM
60
197
0
28 Mar 2021
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
107
1,034
0
18 Feb 2020
NLNL: Negative Learning for Noisy Labels
NLNL: Negative Learning for Noisy Labels
Youngdong Kim
Junho Yim
Juseung Yun
Junmo Kim
NoLa
52
277
0
19 Aug 2019
C2AE: Class Conditioned Auto-Encoder for Open-set Recognition
C2AE: Class Conditioned Auto-Encoder for Open-set Recognition
Poojan Oza
Vishal M. Patel
117
324
0
02 Apr 2019
Recent Advances in Open Set Recognition: A Survey
Recent Advances in Open Set Recognition: A Survey
Chuanxing Geng
Sheng-Jun Huang
Songcan Chen
BDLObjD
141
771
0
21 Nov 2018
Deep Facial Expression Recognition: A Survey
Deep Facial Expression Recognition: A Survey
Shan Li
Weihong Deng
192
1,299
0
23 Apr 2018
Random Erasing Data Augmentation
Random Erasing Data Augmentation
Zhun Zhong
Liang Zheng
Guoliang Kang
Shaozi Li
Yi Yang
96
3,644
0
16 Aug 2017
AffectNet: A Database for Facial Expression, Valence, and Arousal
  Computing in the Wild
AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild
A. Mollahosseini
Behzad Hasani
Mohammad H. Mahoor
CVBM
84
1,640
0
14 Aug 2017
A Baseline for Detecting Misclassified and Out-of-Distribution Examples
  in Neural Networks
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Dan Hendrycks
Kevin Gimpel
UQCV
166
3,468
0
07 Oct 2016
Learning Deep Features for Discriminative Localization
Learning Deep Features for Discriminative Localization
Bolei Zhou
A. Khosla
Àgata Lapedriza
A. Oliva
Antonio Torralba
SSLSSegFAtt
253
9,338
0
14 Dec 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
280
19,107
0
20 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for
  Unrecognizable Images
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Anh Totti Nguyen
J. Yosinski
Jeff Clune
AAML
171
3,275
0
05 Dec 2014
Challenges in Representation Learning: A report on three machine
  learning contests
Challenges in Representation Learning: A report on three machine learning contests
Ian Goodfellow
D. Erhan
P. Carrier
Aaron Courville
M. Berk Mirza
...
Jingjing Xie
Lukasz Romaszko
Bing Xu
Chuang Zhang
Yoshua Bengio
CVBM
137
1,619
0
01 Jul 2013
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