A Residual-Based StyleGAN Encoder via Iterative Refinement
restyle-encoder
Official Implementation of our ReStyle paper for both training and evaluation. ReStyle introduces an iterative refinement mechanism which can be applied over different StyleGAN encoders for solving the StyleGAN inversion task.
Different from conventional encoder-based inversion techniques, our residual-based ReStyle scheme incorporates an iterative refinement mechanism to progressively converge to an accurate inversion of real images. For each domain, we show the input image on the left followed by intermediate inversion outputs.
Getting Started
Prerequisites
- Linux or macOS
- NVIDIA GPU + CUDA CuDNN (CPU may be possible with some modifications, but is not inherently supported)
- Python 3
Installation
- Dependencies:
We recommend running this repository using Anaconda.
All dependencies for defining the environment are provided inenvironment/restyle_env.yaml.
Pretrained Models
In this repository, we