expression-recognition

一个拍照做题程序。输入一张包含数学计算题的图片，输出识别出的数学计算式以及计算结果。This is a mathematic expression recognition project.

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

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.

A systematic comparison of different machine learning & deep learning classification approaches applied to the problem of fully automatic recognition of Facial Expressions.

This is the code repository of model TDGAN. Paper: Facial Expression Recognition with Two-branch Disentangled Generative Adversarial Network.

3D facial reconstruction, expression recognition and transfer from monocular RGB images with a deep convolutional auto-encoding neural network

Recognising expression/emotion of unique faces in a video

Emotion recognition system based on LBP-TOP.

🐾 EmotionCube: An intelligent companion robot is designed based on expression recognition and intelligent speech.

MER is a software that identifies and highlights manipulative communication in text from human conversations and AI-generated responses. MER benchmarks language models for manipulative expressions, fostering development of transparency and safety in AI. It also supports manipulation victims by detecting manipulative patterns in human communication.

eMotion-GAN

Face gender, expression, and age estimation

CNN (Convolutional neural network)-based facial expression recognition model (with pretrained weights) implemented with Pytorch

Multi-race 7 Expressions Recognition Dataset

500-Drivers-7-Expression-Recognition-Data

Realtime Expression Recognition in Python using SVM

An expression recognition system created in MATLAB.

Math expression recognition helps to identify handwritten expression visuals and solves them. This is useful when the long expression needs a quick solution.

Detect emotions in real-time using your webcam with this TensorFlow and OpenCV app. Simple UI and accurate detection make it easy to use. 🌟💻

Emotion and Facial Key-Point Detection Classify emotions and detect facial key-points using deep learning! This project combines CNNs and Residual Blocks to predict 15 facial key-points and categorize facial expressions into five emotions: Angry, Disgust, Sad, Happy, and Surprise.