Micro-Expression Recognition
15 papers with code • 1 benchmarks • 1 datasets
Facial Micro-Expression Recognition is a challenging task in identifying suppressed emotion in a high-stake environment, often comes in very brief duration and subtle changes.
CASME II
Latest papers with no code
Meta-Auxiliary Learning for Micro-Expression Recognition
Micro-expressions (MEs) are involuntary movements revealing people's hidden feelings, which has attracted numerous interests for its objectivity in emotion detection.
An Empirical Study of Super-resolution on Low-resolution Micro-expression Recognition
Micro-expression recognition (MER) in low-resolution (LR) scenarios presents an important and complex challenge, particularly for practical applications such as group MER in crowded environments.
Learning to Rank Onset-Occurring-Offset Representations for Micro-Expression Recognition
This paper focuses on the research of micro-expression recognition (MER) and proposes a flexible and reliable deep learning method called learning to rank onset-occurring-offset representations (LTR3O).
Catching Elusive Depression via Facial Micro-Expression Recognition
Depression is a common mental health disorder that can cause consequential symptoms with continuously depressed mood that leads to emotional distress.
Feature Representation Learning with Adaptive Displacement Generation and Transformer Fusion for Micro-Expression Recognition
Micro-expressions are spontaneous, rapid and subtle facial movements that can neither be forged nor suppressed.
Efficient Neural Architecture Search for Emotion Recognition
In this paper, we proposed to search for a highly efficient and robust neural architecture for both macro and micro-level facial expression recognition.
Prior Information based Decomposition and Reconstruction Learning for Micro-Expression Recognition
To solve this issue, driven by the prior information that the category of ME can be inferred by the relationship between the actions of facial different components, this work designs a novel model that can conform to this prior information and learn ME movement features in an interpretable way.
Multi-scale multi-modal micro-expression recognition algorithm based on transformer
A micro-expression is a spontaneous unconscious facial muscle movement that can reveal the true emotions people attempt to hide.
SelfME: Self-Supervised Motion Learning for Micro-Expression Recognition
To overcome this limitation, we proposed a novel MER framework using self-supervised learning to extract facial motion for ME (SelfME).
Deep Insights of Learning based Micro Expression Recognition: A Perspective on Promises, Challenges and Research Needs
Therefore, this paper aims to provide a deep insight into the DL-based MER frameworks with a perspective on promises in network model designing, experimental strategies, challenges, and research needs.
