A CNN based pytorch implementation on facial expression recognition (FER2013 and CK+), achieving 73.112% (state-of-the-art) in FER2013 and 94.64% in CK+ dataset

A deep neural net toolkit for emotion analysis via Facial Expression Recognition (FER)

TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow

A Lightweight Deep Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Framework for Python

😆 A voice chatbot that can imitate your expression. OpenCV+Dlib+Live2D+Moments Recorder+Turing Robot+Iflytek IAT+Iflytek TTS

MicroExpNet: An Extremely Small and Fast Model For Expression Recognition From Frontal Face Images

Training SVM classifier to recognize people expressions (emotions) on Fer2013 dataset

Pytorch implementation of Multi-View Dynamic Facial Action Unit Detection, Image and Vision Computing (2018)

Classify each facial image into one of the seven facial emotion categories considered using CNN based on https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge

Recognizes the facial emotion and overlays emoji, equivalent to the emotion, on the persons face.

A cool emotion detector using your laptop/desktop webcam

The main purpose of the project - recognition of emotions based on facial expressions. Cohn-Kanade data set (http://www.pitt.edu/~emotion/ck-spread.htm) is used for explorations and training

Facial Expression Recognition with a deep neural network as a PyPI package

Code for BMVC paper "Joint Action Unit localisation and intensity estimation through heatmap regression"

Human Emotion Analysis using facial expressions in real-time from webcam feed. Based on the dataset from Kaggle's Facial Emotion Recognition Challenge.

Facial Expression Recognition on FER2013, Image Classification in ImageNet

FERAtt: Facial Expression Recognition with Attention Net

Official PyTorch Implementation of 'Facial Motion Prior Networks for Facial Expression Recognition', VCIP 2019, Oral

Apache MXNet Gluon implementation for state of the art FER+ paper for Facial Emotion Recognition - https://arxiv.org/abs/1608.01041

Group Emotion Recognition using deep neural networks and Bayesian classifiers.

FER using CNN

The python code detects different landmarks on the face and predicts the emotions such as smile based on it. It automatically takes a photo of that person when he smiles. Also when the two eyebrows are lifted up, the system plays a music automatically and the music stops when you blink your right eye.

facial emotion recognition with CNN and LSTM

Real-time facial expression recognition and fast face detection based on Keras CNN. Training and testing on both Fer2013 and CK+ facial expression data sets have achieved good results. The speed is 78 fps on NVIDIA 1080Ti. If only face detection is performed, the speed can reach 158 fps. Finally, an emotional monitoring system was developed based on it.

A Pytorch Implementation of FER( facial expression recognition )

Tackling the kaggle problem of Facial Expression Recognition Challenge

Facial Expression Recognition in android where the predictive model built in tensorflow using convolutional neural network

Facial-Expression-Recognition using tensorflow

Greedy Search for Descriptive Spatial Face Features