Facial Expression Recognition
Facial expression recognition is the task of classifying the expressions on face images into various categories such as anger, fear, surprise, sadness, happiness and so on.
( Image credit: DeXpression )
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Subtasks
Greatest papers with code
Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution
Crowd sourcing has become a widely adopted scheme to collect ground truth labels.
MicroExpNet: An Extremely Small and Fast Model For Expression Recognition From Face Images
On the other hand, KD is proved to be useful for model compression for the FER problem, and we discovered that its effects gets more and more significant with the decreasing model size.
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.
Covariance Pooling For Facial Expression Recognition
In this work, we explore the benefits of using a man- ifold network structure for covariance pooling to improve facial expression recognition.
Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition
• kaiwang960112/Challenge-condition-FER-dataset
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Extensive experiments show that our RAN and region biased loss largely improve the performance of FER with occlusion and variant pose.
Challenges in Representation Learning: A report on three machine learning contests
• justinshenk/fer
• 
The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge.
SOTA for Facial Expression Recognition on FER2013 (using extra training data)
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.
FERAtt: Facial Expression Recognition with Attention Net
We present a new end-to-end network architecture for facial expression recognition with an attention model.
4DFAB: A Large Scale 4D Facial Expression Database for Biometric Applications
4DFAB contains recordings of 180 subjects captured in four different sessions spanning over a five-year period.
A Compact Embedding for Facial Expression Similarity
CVPR 2019
• GerardLiu96/FECNet
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Most of the existing work on automatic facial expression analysis focuses on discrete emotion recognition, or facial action unit detection.
ACTION UNIT DETECTION EMOTION RECOGNITION FACIAL EXPRESSION RECOGNITION