tg-bomze/Face-Depixelizer
A face super-resolution tool that upscales low-resolution face images using StyleGAN and the PULSE generative model.
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This repository implements a face depixelizer based on the PULSE (Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models) paper. Given a low-resolution face image, it searches the latent space of StyleGAN to find high-resolution outputs that downscale correctly to match the input. The system uses a generative model to produce perceptually realistic face images from pixelated inputs, providing Jupyter notebooks for running inference on Google Colab.
Frequently asked
- What is tg-bomze/Face-Depixelizer?
- A face super-resolution tool that upscales low-resolution face images using StyleGAN and the PULSE generative model.
- Is Face-Depixelizer open source?
- Yes — tg-bomze/Face-Depixelizer is an open-source project tracked on heatdrop.
- What language is Face-Depixelizer written in?
- tg-bomze/Face-Depixelizer is primarily written in Jupyter Notebook.
- How popular is Face-Depixelizer?
- tg-bomze/Face-Depixelizer has 2.6k stars on GitHub.
- Where can I find Face-Depixelizer?
- tg-bomze/Face-Depixelizer is on GitHub at https://github.com/tg-bomze/Face-Depixelizer.