Deep Learning for Micro-expression Recognition: A Survey
Micro-expressions (MEs) are involuntary facial movements revealing people's hidden feelings in high-stake situations and have practical importance in medical treatment, national security, interrogations and many human-computer interaction systems. Early methods for MER mainly based on traditional appearance and geometry features. Recently, with the success of deep learning (DL) in various fields, neural networks have received increasing interests in MER. Different from macro-expressions, MEs are spontaneous, subtle, and rapid facial movements, leading to difficult data collection, thus have small-scale datasets. DL based MER becomes challenging due to above ME characters. To date, various DL approaches have been proposed to solve the ME issues and improve MER performance. In this survey, we provide a comprehensive review of deep micro-expression recognition (MER), including datasets, deep MER pipeline, and the bench-marking of most influential methods. This survey defines a new taxonomy for the field, encompassing all aspects of MER based on DL. For each aspect, the basic approaches and advanced developments are summarized and discussed. In addition, we conclude the remaining challenges and and potential directions for the design of robust deep MER systems. To the best of our knowledge, this is the first survey of deep MER methods, and this survey can serve as a reference point for future MER research.
Code (0)
등록된 구현이 없습니다.
Tasks
Deep LearningMicro Expression RecognitionMicro-Expression RecognitionSurveySimilar Papers 제목 키워드 기반
An Overview of Facial Micro-Expression Analysis: Data, Methodology and Challenge
Facial micro-expressions indicate brief and subtle facial movements that appear during emotional communication. In comparison to macro-expressions, micro-expressions are more challenging to be analyzed due to the short s…
DiversityMicro Expression RecognitionMicro-Expression RecognitionMicro-Expression Spotting+1Video-based Facial Micro-Expression Analysis: A Survey of Datasets, Features and Algorithms
Unlike the conventional facial expressions, micro-expressions are involuntary and transient facial expressions capable of revealing the genuine emotions that people attempt to hide. Therefore, they can provide important …
SurveyA Survey of Automatic Facial Micro-expression Analysis: Databases, Methods and Challenges
Over the last few years, automatic facial micro-expression analysis has garnered increasing attention from experts across different disciplines because of its potential applications in various fields such as clinical dia…
Micro-Expression Recognition Based on Attribute Information Embedding and Cross-modal Contrastive Learning
Facial micro-expressions recognition has attracted much attention recently. Micro-expressions have the characteristics of short duration and low intensity, and it is difficult to train a high-performance classifier with …
AttributeContrastive LearningMicro Expression RecognitionMicro-Expression RecognitionFeature refinement: An expression-specific feature learning and fusion method for micro-expression recognition
Micro-Expression Recognition has become challenging, as it is extremely difficult to extract the subtle facial changes of micro-expressions. Recently, several approaches proposed several expression-shared features algori…
Micro Expression RecognitionMicro-Expression RecognitionOptical Flow Estimation