Real-time Facial Emotion Detection using deep learning

libfaceid is a research framework for prototyping of face recognition solutions. It seamlessly integrates multiple detection, recognition and liveness models w/ speech synthesis and speech recognition.

MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation

A real time Multimodal Emotion Recognition web app for text, sound and video inputs

Reading list for Awesome Sentiment Analysis papers

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

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

An emotion classifier of text containing technical content from the SE domain

Emotion analyzer for Japanese text

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

Emotion detection on browser using TensorFlow.js

Response generation giving specific emotion.

Group Emotion Recognition using deep neural networks and Bayesian classifiers.

Multimodal sentiment analysis using hierarchical fusion with context modeling

face liveness detection activate, the script asks the person to generate an action, for example one of the actions they may ask you to do is smile, turn your face to the right, get angry, blink, etc. The actions are requested randomly, after fulfilling all the actions it generates a message saying "liveness successful" or "liveness fail"

Emotion Detection in Speech - using SVM Classification

🤓 Simple Emotion Detection Neural Network made with brain.js for an article on Hackdoor

A Deep Learning application to recognize emotion from facial expressions.

Emotion detection on multiparty dialogue.

Deep-learning system presented in "EmoSence at SemEval-2019 Task 3: Bidirectional LSTM Network for Contextual Emotion Detection in Textual Conversations" at SemEval-2019.

Predicting emotions based on speech audio samples of American English, German and British English languages using Support Vector Machine, K-Nearest Neighbor, Random Forest and Recurrent Neural Network. Analyzing the performance of each model based on the dataset.

Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits

An emotion extraction system for images, that extracts emotion which will be felt by the user of viewing the image, representing them in a 2-Dimensional space that represents Arousal and Valence.

DEmoClassi stands for Demographic (age, gender, race) and Emotions (happy, sad, angry, ...) Classification from face images, using deep learning.

This is a Human Attributes Detection program with facial features extraction. It detects facial coordinates using FaceNet model and uses MXNet facial attribute extraction model for extracting 40 types of facial attributes. This solution also detects Emotion, Age and Gender along with facial attributes.

An AI Tool to record expressions of users as they watch a video and then visualize the funniest parts of it!

Emotion classification has always been a very challenging task in Computer Vision. Using the SSD object detection algorithm to extract the face in an image and using the FER 2013 released by Kaggle, this project couples a deep learning based face detector and an emotion classification DNN to classify the six/seven basic human emotions.

This is a Python 3 based project to display facial expressions by performing fast & accurate face detection with OpenCV using a pre-trained deep learning face detector model shipped with the library.

Emotion recognition from face

libfaceid is a research framework for fast prototyping of face recognition solutions. It seamlessly integrates multiple face detection, face recognition and liveness detection models. It also includes face landmark detection, age detection, gender detection, emotion detection, wakeword/triggerword/hotword detection and text-to-speech synthesis for voice capability).