How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)

This repository implements a demo of the networks described in "How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)" paper. Please visit our webpage or read bellow for instructions on how to run the code and access the dataset.

Note: If you are interested in a binarized version, capable of running on devices with limited resources please also check https://github.com/1adrianb/binary-face-alignment for a demo.

Requirments

• Install the latest Torch7 version (for Windows, please follow the instructions available here)
• Install python 2.7.x

Packages

• cutorch
• nn
• nngraph
• cudnn
• xlua
• image
• paths
• fb.python

Setup

Clone the github repository and install all the dependencies mentiones above.

git  clone https://github.com/1adrianb/2D-and-3D-face-alignment
cd 2D-and-3D-face-alignment

Usage

In order to run the demo please download the required models available bellow and the associated data.

th main.lua

In order to see all the available options please run:

th main.lua --help

Pretrained models

2D-FAN - trained on 300W-LP and finetuned on iBUG training set.

3D-FAN - trained on 300W-LP

2D-to-3D-FAN - trained on 300W-LP

Dataset

You can download the annotations alongside the images used by visiting our page.