Face Parsing

1. Face parsing introduction

Face parsing address the task that how to parse facial components from face images. We utiize BiseNet to handle this problem and focus on computing the pixel-wise label map of a face image. It is useful for a variety of tasks, including recognition, animation, and synthesis. This application is now working in our makeup transfer model.

2. How to use

2.1 Test

Runing the following command to complete the face parsing task. The output results will be the segmanted face components mask for the input image.

cd applications
python tools/face_parse.py --input_image ../docs/imgs/face.png

params:

• input_image: path of the input face image

Results

4. Reference

@misc{yu2018bisenet,
      title={BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation},
      author={Changqian Yu and Jingbo Wang and Chao Peng and Changxin Gao and Gang Yu and Nong Sang},
      year={2018},
      eprint={1808.00897},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}