Cross-Database Micro-Expression Recognition Based on a Dual-Stream Convolutional Neural Network
Cross-database micro-expression recognition (CDMER) is a difficult task, where the target (testing) and source (training) samples come from different micro-expression (ME) databases, […]
Informative Class-Conditioned Feature Alignment for Unsupervised Domain Adaptation
The goal of unsupervised domain adaptation is to learn a task classifier that performs well for the unlabeled target domain by borrowing […]
Deep ladder reconstruction-classification network for unsupervised domain adaptation
Unsupervised Domain Adaptation aims to learn a classifier for an unlabeled target domain by transferring knowledge from a labeled source domain. Most […]
Joint Clustering and Discriminative Feature Alignment for Unsupervised Domain Adaptation
Unsupervised Domain Adaptation (UDA) aims to learn a classifier for the unlabeled target domain by leveraging knowledge from a labeled source domain […]
Informative Feature Disentanglement for Unsupervised Domain Adaptation
Unsupervised Domain Adaptation (UDA) aims at learning a classifier for an unlabeled target domain by transferring knowledge from a labeled source domain […]
Unsupervised Cross-Database Micro-Expression Recognition Using Target-Adapted Least-Squares Regression
Over the past several years, the research of micro-expression recognition (MER) has become an active topic in affective computing and computer vision […]
Cross-Database Micro-Expression Recognition
Cross-database micro-expression recognition (CDMER) is one of recently emerging and interesting problems in micro-expression analysis. CDMER is more challenging than the conventional […]
Domain Regeneration for Cross-Database Micro-Expression Recognition
Recently, micro-expression recognition has attracted lots of researchers’ attention due to its potential value in many practical applications, e.g., lie detection. In […]