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.
Most implemented papers
Data Leakage and Evaluation Issues in Micro-Expression Analysis
Micro-expressions have drawn increasing interest lately due to various potential applications.
Micron-BERT: BERT-based Facial Micro-Expression Recognition
By incorporating these components into an end-to-end deep network, the proposed $\mu$-BERT significantly outperforms all previous work in various micro-expression tasks.
HTNet for micro-expression recognition
The transformer layer is used to focus on representing local minor muscle movement with local self-attention in each area.
GPT-4V with Emotion: A Zero-shot Benchmark for Generalized Emotion Recognition
To bridge this gap, we present the quantitative evaluation results of GPT-4V on 21 benchmark datasets covering 6 tasks: visual sentiment analysis, tweet sentiment analysis, micro-expression recognition, facial emotion recognition, dynamic facial emotion recognition, and multimodal emotion recognition.
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 MLMs in human-centric computing.