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Uncertain facial expression recognition via multi-task assisted correction
Deep models for facial expression recognition achieve high performance by training on
large-scale labeled data. However, publicly available datasets contain uncertain facial …
large-scale labeled data. However, publicly available datasets contain uncertain facial …
Low-resolution object recognition with cross-resolution relational contrastive distillation
Recognizing objects in low-resolution images is a challenging task due to the lack of
informative details. Recent studies have shown that knowledge distillation approaches can …
informative details. Recent studies have shown that knowledge distillation approaches can …
Semi-supervised feature learning for disjoint hyperspectral imagery classification
With the introduction of spatial-spectral fusion and deep learning, the classification
performance of hyperspectral imagery (HSI) has been promoted greatly. For some widely …
performance of hyperspectral imagery (HSI) has been promoted greatly. For some widely …
CalD3r and MenD3s: Spontaneous 3D facial expression databases
In the last couple of decades, the research on 3D facial expression recognition has been
fostered by the creation of tailored databases containing prototypical expressions of different …
fostered by the creation of tailored databases containing prototypical expressions of different …
From Macro to Micro: Boosting micro-expression recognition via pre-training on macro-expression videos
Micro-expression recognition (MER) has drawn increasing attention in recent years due to
its potential applications in intelligent medical and lie detection. However, the shortage of …
its potential applications in intelligent medical and lie detection. However, the shortage of …
CSLSEP: an ensemble pruning algorithm based on clustering soft label and sorting for facial expression recognition
S Huang, D Li, Z Zhang, Y Wu, Y Tang, X Chen… - Multimedia Systems, 2023 - Springer
Applying ensemble learning to facial expression recognition is an important research field
nowadays, but all may not be better than many, the redundant learners in the classifier pool …
nowadays, but all may not be better than many, the redundant learners in the classifier pool …
Exploring holistic discriminative representation for micro-expression recognition via contrastive learning
Recently, deep learning-based micro-expression recognition (MER) has been remarkably
successful in the affective computing and computer vision communities. However, the most …
successful in the affective computing and computer vision communities. However, the most …
Downstream-pretext domain knowledge traceback for active learning
Active learning (AL) is designed to construct a high-quality labeled dataset by iteratively
selecting the most informative samples. Such sampling heavily relies on data …
selecting the most informative samples. Such sampling heavily relies on data …
Active learning with label quality control
Training deep neural networks requires a large number of labeled samples, which are
typically provided by crowdsourced workers or professionals at a high cost. To obtain …
typically provided by crowdsourced workers or professionals at a high cost. To obtain …
Decoupling facial motion features and identity features for micro-expression recognition
T **e, G Sun, H Sun, Q Lin, X Ben - PeerJ Computer Science, 2022 - peerj.com
Background Micro-expression is a kind of expression produced by people spontaneously
and unconsciously when receiving stimulus. It has the characteristics of low intensity and …
and unconsciously when receiving stimulus. It has the characteristics of low intensity and …