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
Objective Class-based Micro-Expression Recognition through Simultaneous Action Unit Detection and Feature Aggregation
Specifically, we propose two new strategies in our AU detection module for more effective AU feature learning: the attention mechanism and the balanced detection loss function.
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.
MERANet: Facial Micro-Expression Recognition using 3D Residual Attention Network
The proposed model takes advantage of spatial-temporal attention and channel attention together, to learn deeper fine-grained subtle features for classification of emotions.
A Multi-stream Convolutional Neural Network for Micro-expression Recognition Using Optical Flow and EVM
On the other hand, some methods based on deep learning also cannot get high accuracy due to problems such as the imbalance of databases.
SMA-STN: Segmented Movement-Attending Spatiotemporal Network forMicro-Expression Recognition
Correctly perceiving micro-expression is difficult since micro-expression is an involuntary, repressed, and subtle facial expression, and efficiently revealing the subtle movement changes and capturing the significant segments in a micro-expression sequence is the key to micro-expression recognition (MER).
Revealing the Invisible with Model and Data Shrinking for Composite-database Micro-expression Recognition
In this paper, we analyze the influence of learning complexity, including the input complexity and model complexity, and discover that the lower-resolution input data and shallower-architecture model are helpful to ease the degradation of deep models in composite-database task.
Non-Linearities Improve OrigiNet based on Active Imaging for Micro Expression Recognition
However, existing networks fail to establish a relationship between spatial features of facial appearance and temporal variations of facial dynamics.
Mean Oriented Riesz Features for Micro Expression Classification
Micro-expressions are brief and subtle facial expressions that go on and off the face in a fraction of a second.
MER-GCN: Micro Expression Recognition Based on Relation Modeling with Graph Convolutional Network
Micro-Expression (ME) is the spontaneous, involuntary movement of a face that can reveal the true feeling.
Autonomous Apex Detection and Micro-Expression Recognition using Proposed Diagonal Planes
In fact, we utilize it after motion magnification for feature extraction in apex detection task.
