There are 26 repositories under emotion-detection topic.
Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition
Real-time Facial Emotion Detection using deep learning
A real time Multimodal Emotion Recognition web app for text, sound and video inputs
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation
FaceAPI: AI-powered Face Detection & Rotation Tracking, Face Description & Recognition, Age & Gender & Emotion Prediction for Browser and NodeJS using TensorFlow/JS
🔥🔥The pytorch implement of the head pose estimation(yaw,roll,pitch) and emotion detection with SOTA performance in real time.Easy to deploy, easy to use, and high accuracy.Solve all problems of face detection at one time.(极简,极快,高效是我们的宗旨)
Efficient face emotion recognition in photos and videos
Reading list for Awesome Sentiment Analysis papers
Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras
Large-Scale Selfie Video Dataset (L-SVD): A Benchmark for Emotion Recognition
Facial Expression Recognition with a deep neural network as a PyPI package
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"
Official implementation of the paper "Estimation of continuous valence and arousal levels from faces in naturalistic conditions", Antoine Toisoul, Jean Kossaifi, Adrian Bulat, Georgios Tzimiropoulos and Maja Pantic, Nature Machine Intelligence, 2021
Speech Emotion Classification with novel Parallel CNN-Transformer model built with PyTorch, plus thorough explanations of CNNs, Transformers, and everything in between
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.
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 emotion classifier of text containing technical content from the SE domain
Voice stress analysis (VSA) aims to differentiate between stressed and non-stressed outputs in response to stimuli (e.g., questions posed), with high stress seen as an indication of deception. In this work, we propose a deep learning-based psychological stress detection model using speech signals. With increasing demands for communication between humans and intelligent systems, automatic stress detection is becoming an interesting research topic. Stress can be reliably detected by measuring the level of specific hormones (e.g., cortisol), but this is not a convenient method for the detection of stress in human- machine interactions. The proposed algorithm first extracts Mel- filter bank coefficients using pre-processed speech data and then predicts the status of stress output using a binary decision criterion (i.e., stressed or unstressed) using CNN (Convolutional Neural Network) and dense fully connected layer networks.
Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits
Response generation giving specific emotion.
An in-depth analysis of audio classification on the RAVDESS dataset. Feature engineering, hyperparameter optimization, model evaluation, and cross-validation with a variety of ML techniques and MLP
Emotion detection on browser using TensorFlow.js
XED multilingual emotion datasets
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.
😎 Awesome lists about Speech Emotion Recognition
Automate detection of different emotions from paragraphs and predict overall emotion.
Group Emotion Recognition using deep neural networks and Bayesian classifiers.
An Exciting Deep Learning-based Flask web app that predicts the Facial Expressions of users and also does Graphical Visualization of the Expressions.
Predicting various emotion in human speech signal by detecting different speech components affected by human emotion.
Multimodal sentiment analysis using hierarchical fusion with context modeling
[ICASSP 2023] FedAudio: A Federated Learning Benchmark for Audio and Speech Tasks