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
Most implemented papers
Enriched Long-term Recurrent Convolutional Network for Facial Micro-Expression Recognition
IcedDoggie/Micro-Expression-with-Deep-Learning
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Facial micro-expression (ME) recognition has posed a huge challenge to researchers for its subtlety in motion and limited databases.
Dual-stream shallow networks for facial micro-expression recognition
Justin900429/PyTorch-DSSN-MER
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2019 IEEE International Conference on Image Processing (ICIP) 2019
Micro-expressions are spontaneous, brief and subtle facial muscle movements that exposes underlying emotions.
GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective Computing
In conclusion, this paper provides valuable insights into the potential applications and challenges of MLLMs in human-centric computing.
Micro-Attention for Micro-Expression recognition
The existence of micro expression in small-local areas on face and limited size of available databases still constrain the recognition accuracy on such emotional facial behavior.
Shallow Triple Stream Three-dimensional CNN (STSTNet) for Micro-expression Recognition
In the recent year, state-of-the-art for facial micro-expression recognition have been significantly advanced by deep neural networks.
Spontaneous Facial Micro-Expression Recognition using 3D Spatiotemporal Convolutional Neural Networks
This paper proposes two 3D-CNN methods: MicroExpSTCNN and MicroExpFuseNet, for spontaneous facial micro-expression recognition by exploiting the spatiotemporal information in CNN framework.
A Novel Apex-Time Network for Cross-Dataset Micro-Expression Recognition
Mvrjustid/ACII19-Apex-Time-Network
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As researchers working on such topics are moving to learn from the nature of micro-expression, the practice of using deep learning techniques has evolved from processing the entire video clip of micro-expression to the recognition on apex frame.
ICE-GAN: Identity-aware and Capsule-Enhanced GAN with Graph-based Reasoning for Micro-Expression Recognition and Synthesis
Micro-expressions are reflections of people's true feelings and motives, which attract an increasing number of researchers into the study of automatic facial micro-expression recognition.
Seeking Salient Facial Regions for Cross-Database Micro-Expression Recognition
To solve these problems, this paper proposes a novel Transfer Group Sparse Regression method, namely TGSR, which aims to 1) optimize the measurement and better alleviate the difference between the source and target databases, and 2) highlight the valid facial regions to enhance extracted features, by the operation of selecting the group features from the raw face feature, where each region is associated with a group of raw face feature, i. e., the salient facial region selection.
How to Synthesize a Large-Scale and Trainable Micro-Expression Dataset?
liuyvchi/mie-x
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To this end, we develop a protocol to automatically synthesize large scale MiE training data that allow us to train improved recognition models for real-world test data.
