Facial Expression Recognition
127 papers with code • 3 benchmarks • 3 datasets
Libraries
Use these libraries to find Facial Expression Recognition models and implementationsMost implemented papers
Consensual Collaborative Training And Knowledge Distillation Based Facial Expression Recognition Under Noisy Annotations
A dynamic transition mechanism is used to move from supervision loss in early learning to consistency loss for consensus of predictions among networks in the later stage.
Greedy Search for Descriptive Spatial Face Features
Spatial features are derived from displacements of facial landmarks, and carry geometric information.
Frame attention networks for facial expression recognition in videos
The feature embedding module is a deep Convolutional Neural Network (CNN) which embeds face images into feature vectors.
Suppressing Uncertainties for Large-Scale Facial Expression Recognition
Annotating a qualitative large-scale facial expression dataset is extremely difficult due to the uncertainties caused by ambiguous facial expressions, low-quality facial images, and the subjectiveness of annotators.
Facial Expression Recognition with Deep Learning
One of the most universal ways that people communicate is through facial expressions.
Graph Convolution with Low-rank Learnable Local Filters
Recent deep models using graph convolutions provide an appropriate framework to handle such non-Euclidean data, but many of them, particularly those based on global graph Laplacians, lack expressiveness to capture local features required for representation of signals lying on the non-Euclidean grid.
Affect Expression Behaviour Analysis in the Wild using Spatio-Channel Attention and Complementary Context Information
Facial expression recognition(FER) in the wild is crucial for building reliable human-computer interactive systems.
Distract Your Attention: Multi-head Cross Attention Network for Facial Expression Recognition
To address these issues, we propose our DAN with three key components: Feature Clustering Network (FCN), Multi-head cross Attention Network (MAN), and Attention Fusion Network (AFN).
Complete Face Recovery GAN: Unsupervised Joint Face Rotation and De-Occlusion From a Single-View Image
In addition, the lack of high-quality paired data remains an obstacle for both methods.
Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network
Facial expressions are a form of non-verbal communication that humans perform seamlessly for meaningful transfer of information.