Pytorch implementation of Conditional image-to-image translation [1] (CVPR 2018)
- Parameters without information in the paper were set arbitrarily. (I could not find the supplementary document)
python train.py --dataset dataset The following shows basic folder structure.
├── data ├── dataset # not included in this repo ├── trainA ├── aaa.png ├── bbb.jpg └── ... ├── trainB ├── ccc.png ├── ddd.jpg └── ... ├── testA ├── eee.png ├── fff.jpg └── ... └── testB ├── ggg.png ├── hhh.jpg └── ... ├── train.py # training code ├── utils.py ├── networks.py └── name_results # results to be saved here 
| InputA - InputB - A2B - B2A (this repo) |
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- NVIDIA GTX 1080 ti
- cuda 8.0
- python 3.5.3
- pytorch 0.4.0
- torchvision 0.2.1
[1] Lin, Jianxin, et al. "Conditional image-to-image translation." The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)(July 2018). 2018.
(Full paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_Conditional_Image-to-Image_Translation_CVPR_2018_paper.pdf)