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.
State-of-the-art leaderboards
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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 Frontal Face Images
This paper is aimed at creating extremely small and fast convolutional neural networks (CNN) for the problem of facial expression recognition (FER) from frontal face images.
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
Extensive experiments show that our RAN and region biased loss largely improve the performance of FER with occlusion and variant pose.
Spontaneous Facial Micro-Expression Recognition using 3D Spatiotemporal Convolutional Neural Networks
• bogireddytejareddy/micro-expression-recognition
This paper proposes two 3D-CNN methods: MicroExpSTCNN and MicroExpFuseNet, for spontaneous facial micro-expression recognition by exploiting the spatiotemporal information in CNN framework.
Challenges in Representation Learning: A report on three machine learning contests
• justinshenk/fer
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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.
FERAtt: Facial Expression Recognition with Attention Net
We present a new end-to-end network architecture for facial expression recognition with an attention model.
Engagement Recognition using Deep Learning and Facial Expression
• omidnezami/Engagement-Recognition
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This paper presents a deep learning model to improve engagement recognition from face images captured in the wild that overcomes the data sparsity challenge by pre-training on readily available basic facial expression data, before training on specialised engagement data.
Greedy Search for Descriptive Spatial Face Features
• bbenligiray/greedy-face-features
Spatial features are derived from displacements of facial landmarks, and carry geometric information.
DeXpression: Deep Convolutional Neural Network for Expression Recognition
• MaxLikesMath/DeepLearningImplementations
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The proposed architecture achieves 99. 6% for CKP and 98. 63% for MMI, therefore performing better than the state of the art using CNNs.
SOTA for Facial Expression Recognition on MMI