PyTorch Implementation of ECCV 2020 Spotlight TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images

Last update: Dec 09, 2022

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Overview

TuiGAN-PyTorch

Official PyTorch Implementation of "TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images" (ECCV 2020 Spotlight)

TuiGAN's applications

TuiGAN can be use for various computer vision tasks ranging from image style transfer to object transformation and appearance transformation:

Usage

Install dependencies

python -m pip install -r requirements.txt

Our code was tested with python 3.6 and PyToch 1.0.0 or 1.2.0

Train

To train TuiGAN model on two unpaired images, put the first training image under datas/task_name/trainA and the second training image under datas/task_name/trainB, and run

python train.py --input_name 
   
     --root

For example,

python train.py --input_name apple --root datas/apple

Comparison Results

General Unsupervised Image-to-Image Translation

Image Style Transfer

Animal Face Translation

Painting-to-Image Translation

More Results

Art Style Transfer

Photorealistic Style Transfer

Animal Face Translation

Owner

Ph.D. Candidate of University of Science and Technology of China

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PyTorch Implementation of ECCV 2020 Spotlight TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images

Related tags

Overview

TuiGAN-PyTorch

TuiGAN's applications

Usage

Install dependencies

Train

Comparison Results

General Unsupervised Image-to-Image Translation

Image Style Transfer

Animal Face Translation

Painting-to-Image Translation

More Results

Art Style Transfer

Photorealistic Style Transfer

Animal Face Translation

Owner

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