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Learning One-shot Face Reenactment

Official test script for 2019 BMVC paper 'Learning One-shot Face Reenactment' in PyTorch.

image

Installation

Requirements

  • Linux
  • Python 3.6
  • PyTorch 1.0+
  • CUDA 9.0+
  • GCC 4.9+

Easy Install

pip install -r requirements.txt

Getting Started

Prepare Data

It is recommended to symlink the dataset root to $PROJECT/data.

Project
├── data
│   ├── poseGuide
│   │   ├── imgs
│   │   ├── lms
│   ├── reference
│   │   ├── imgs
│   │   ├── lms

  • imgs : store images that match lms

  • lms : store landmarks extracted from images

    • format : 106 common facial key points & 20+20 gaze key points

    image

Example input data is organized in folder 'data'. Please organize your data in the format the same as the example input data if you want to test with your own data.

Output images are saved in folder 'output'.

Inference with pretrained model

python test.py --pose_path PATH/TO/POSE/GUIDE/IMG/DIR --ref_path PATH/TO/REF/IMG/DIR --pose_lms PATH/TO/POSE/LANDMARK/FILE --ref_lms PATH/TO/REF/LANDMARK/FILE

output sequence: 
		ref1-pose1, ref1-pose2,  ref1-pose3, ... &
		ref2-pose1, ref2-pose2,  ref2-pose3, ... &
		ref3-pose1, ref3-pose2,  ref3-pose3, ... &
		    .				
		    .				
		    .

Pretrained model

You can download the model from here

Visualization of results

You can download our sample data and corresponding results from here