Synthesizing Normalized Faces From Facial Identity Features (Additional Results B.3 Section Implementation Only)

This repository provides a Python implementation of the CVPR 2017 Paper - Synthesizing Normalized Faces From Facial Identity Features (Additional Results B.3 Implementation Only). Only Fitting Texture part is implemented which is mentioned in Additional Results Section B.3 of the paper.

Paper

Synthesizing Normalized Faces From Facial Identity Features

Dependencies

Python >= 3.5
- Numpy -> pip install numpy
- Scipy -> pip install scipy

Usage

1. Cloning the repository

git clone https://github.com/nabeel3133/3D-texture-fitting.git
cd 3D-texture-fitting

2. Downloading the model

BFM09: Basel Face Model 2009
- After you have acquired BFM, extract the BaselFaceModel.tgz and go toPublicMM1 folder, copy 01_MorphableModel.mat, BFM_exp_idx.mat and paste it in ./3D-texture-fitting/configs folder.

3. Running the code

Run the main.py with obj output from ddfa as input

python main.py -o ./samples/test.obj

If you can see the following output log in terminal, you ran it successfully.

BFM Mapping for Texture Prediction Started...
BFM Mapping for Texture Prediction Completed
Predicting Ear and Neck Texture...
Predicting Ear and Neck Texture Completed
Dump to ./samples/output.obj
Dump to ./samples/output.ply

Two output files (obj and ply) will be saved in 3D-texture-fitting/samples folder with the name output.obj and output.ply which can be redered by Meshlab or Microsoft 3D Builder.

Citation

If this work is useful for your research or if you use this implementation in your academic projects, please cite the following papers:

Synthesizing Normalized Faces From Facial Identity Features

@misc{cole2017synthesizing,
    title={Synthesizing Normalized Faces from Facial Identity Features},
    author={Forrester Cole and David Belanger and Dilip Krishnan and Aaron Sarna and Inbar Mosseri and William T. Freeman},
    year={2017},
    eprint={1701.04851},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

References

Face Alignment in Full Pose: A 3D Total Solution (Github)

  @misc{3ddfa_cleardusk,
  author =       {Jianzhu Guo, Xiangyu Zhu and Zhen Lei},
  title =        {3DDFA},
  howpublished = {\url{https://github.com/cleardusk/3DDFA}},
  year =         {2018}
}