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StyleMatte: Adversarially-Guided Portrait Matting

[arXiv] [BibTeX] [Gitlab] [Demo]

PWC


Model Zoo and Baselines

State file Size Where to place Download
stylematte_pure.pth 133.6 MB stylematte/checkpoints/ stylematte.zip
stylematte_synth.pth 133.6 MB stylematte/checkpoints/ stylematte.zip
animals.pkl 300.5 MB stylegan3 stylemattegan.zip
humans.pkl 281.1 MB stylegan3 stylemattegan.zip

How to run StyleMatteGAN

To synthesize synthetic dataset of RGBA images, move to stylegan3 and run synthesize.py. You should create conda environment from stylegan3/environment.yml. You can also generate images with different truncation and seed values using gen_images.py .

conda activate stylegan3
cd stylegan3
python synthesize.py

To change image background on synthetic dataset, run

python visualizer.py

In the GUI you can choose model weights, background picture, truncation value and other visualization parameters.

StyleMatteGAN results


How to run StyleMatte

To test our model, change directory to stylematte and run test.py. You can modify test.yaml file for your datasets and models.

cd stylematte
python test.py

The report directory is stylematte/report/. See report examples there.

StyleMatte results


License

Creative Commons License
This work is licensed under a variant of Creative Commons Attribution-ShareAlike 4.0 International License.

Please see the specific license.

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