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

Deep facial expressions recognition using Opencv and Tensorflow. Recognizing facial expressions from images or camera stream

ICPR 2020: Facial Expression Recognition using Residual Masking Network

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

A landmark-driven method on Facial Expression Recognition (FER)

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

Code for the paper "Facial Emotion Recognition: State of the Art Performance on FER2013"

real-time face detection and emotion classification

Lightweight Facial Expression(emotion) Recognition model

Facial Expression Recognition Using CNN and Haar-Cascade

Facial Expression Recognition

Facial expression recognition using Pytorch on FER2013 dataset and create simple app with streamlit

Images and Videos, Real-time Facial Expession Recognition Application with Combine CNN , deep learning features extraction incorporate SIFT, FAST feature .

A facial emotion recognition program implemented in Python using TensorFlow, Keras and OpenCV and trained on the FER2013 dataset with FERPlus' labels.

A jupyter notebook showing how to finetune the vision transformer on a facial expression dataset (FER-2013)

A Deep Learning application to recognize emotion from facial expressions.

We present our facial expression recognition models for fer-2013 dataset

Engagement Detection, including facial detection and emotion recognition, using CNNs/LSTMs.

emotion classification using fer2013 datasets with a Tensorflow CNN model.

Conditional Cycle-Consistent Generative Adversarial Networks (CCycleGAN)