A deep neural net toolkit for emotion analysis via Facial Expression Recognition (FER)
Code for the paper "Facial Emotion Recognition: State of the Art Performance on FER2013"
FERAtt: Facial Expression Recognition with Attention Net
Deep Attentive Center Loss
Lightweight Facial Expression(emotion) Recognition model
Apache MXNet Gluon implementation for state of the art FER+ paper for Facial Emotion Recognition - https://arxiv.org/abs/1608.01041
A Pytorch Implementation of FER( facial expression recognition )
We present our facial expression recognition models for fer-2013 dataset
It's a project of facial emotion recognition.
Recognising expression/emotion of unique faces in a video
Ad-Corre: Adaptive Correlation-Based Loss for Facial Expression Recognition in the Wild
This is an reimplement of the work Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition. This code is based on the original author's code with the following changes. Thanks, Kai Wang.
Project to find one of 9 pre-trained emotions on given photo, video or webcam-stream
Embedded realization of a FER-CNN(face emotion recogniton) based on STM32H7 MCU.
Framework for neuroevolution of output functions
This projected explored the effect of introducing channel and spatial attention mechanisms, namely SEN-Net, ECA-Net, and CBAM to existing CNN vision-based models such as VGGNet, ResNet, and ResNetV2 to perform the Facial Emotion Recognition task.
This repository is devoted to the development of the facial emotion recognition (FER) system as a final bachelor project at the TU/e. Realised by Blazej Manczak. Supervisors: Dr. Laura Astola (Accenture) and Dr. Vlado Menkovski (TU/e)
Experience EmoPy's Facial Expression Recognition from the browser
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