A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
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Updated
Jun 2, 2024 - Python
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
TensorFlow 101: Introduction to Deep Learning
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)
Deep facial expressions recognition using Opencv and Tensorflow. Recognizing facial expressions from images or camera stream
Efficient face emotion recognition in photos and videos
😆 A voice chatbot that can imitate your expression. OpenCV+Dlib+Live2D+Moments Recorder+Turing Robot+Iflytek IAT+Iflytek TTS
ICPR 2020: Facial Expression Recognition using Residual Masking Network
Facial Expression Recognition with a deep neural network as a PyPI package
Automatic 3D Character animation using Pose Estimation and Landmark Generation techniques
An Exciting Deep Learning-based Flask web app that predicts the Facial Expressions of users and also does Graphical Visualization of the Expressions.
Training SVM classifier to recognize people expressions (emotions) on Fer2013 dataset
A landmark-driven method on Facial Expression Recognition (FER)
Face Analysis: Detection, Age Gender Estimation & Recognition
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
Python library for analysing faces using PyTorch
Human Emotion Analysis using facial expressions in real-time from webcam feed. Based on the dataset from Kaggle's Facial Emotion Recognition Challenge.
Recognizes the facial emotion and overlays emoji, equivalent to the emotion, on the persons face.
[AAAI'21] Robust Lightweight Facial Expression Recognition Network with Label Distribution Training
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
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