This is the PyTorch implementation of StyleGAN of All Trades: Image Manipulation withOnly Pretrained StyleGAN.
Abstract:
Recently, StyleGAN has enabled various image manipulation and editing tasks thanks to the high-quality generation and the disentangled latent space. However, additional architectures or task-specific training paradigms are usually required for different tasks. In this work, we take a deeper look at the spatial properties of StyleGAN. We show that with a pretrained StyleGAN along with some operations, without any additional architecture, we can perform comparably to the state-of-the-art methods on various tasks, including image blending, panorama generation, generation from a single image, controllable and local multimodal image to image translation, and attributes transfer.
Everything to get started is in the colab notebook.
If you use this code or ideas from our paper, please cite our paper:
This code borrows from StyleGAN2 by rosalinity