Video Predicting using ConvLSTM and pytorch

The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)

MicroExpNet: An Extremely Small and Fast Model For Expression Recognition From Frontal Face Images

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

Spontaneous Facial Micro Expression Recognition using 3D Spatio-Temporal Convolutional Neural Networks

An awesome face technology repository.

Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network (ECCV 2018)

deep-sdm is appied for face landmark.

Sample projects for Computer Vision with Raspberry Pi and Movidius Neural Compute Stick

A Lightweight Deep Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Framework for Python

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

MIMAMO Net: Integrating Micro- and Macro-motion for Video Emotion Recognition

A simple baseline for one-shot multi-object tracking

Face Analysis Project on MXNet

SeetaFace 6: Newest open and free, full stack face recognization toolkit.

machine learning model that predicts body mass index from face images

Deep Learning Based Free Mobile Real-Time Face Landmark Detector.

Source code of Robust Facial Alignment with Internal Denoising Auto-Encoder

Learning Multi-Domain Convolutional Neural Networks for Visual Tracking

MDNet PyTorch implementation

Python tools for 3D face: 3DMM, Mesh processing(transform, camera, light, render), 3D face representations.

Robust Discriminative Projective Dictionary Pair Learning by Adaptive Representations

mtcnn mxnet C++ implementation

A Lightweight and Efficient Method for Face Age and Gender Estimation Implemented in MXNet

A 68-point Facial landmark at 28-30 FPS on iPhone 6S+. HyperLandmark is get from https://github.com/zeusees/HyperLandmark.

Code for our AAAI'19 paper "Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos"

Full version (training+testing) of implementation of Shizhan Zhu et al.'s CVPR-15 work Face Alignment by Coarse-to-Fine Shape Searching