SpiralNet

This repository provides the official PyTorch implementation of our paper "Spiral Generative Network for Image Extrapolation".

Our paper can be found in https://link.springer.com/chapter/10.1007/978-3-030-58529-7_41.

Prerequisites

• Linux
• Python 3.7
• NVIDIA GPU + CUDA CuDNN

Getting Started

Installation

• Clone this repo:

git clone https://github.com/zhenglab/spiralnet.git
cd spiralnet

• Install PyTorch and 1.0+ and other dependencies (e.g., torchvision).
  • For pip users, please type the command pip install -r requirement.txt.
  • For Conda users, you can create a new Conda environment using conda env create -f environment.yaml.

ImagineGAN

• Training

python train.py --path=$configpath$

For example: python train.py --path=./checkpoints/ImagineGAN/celeba/

• Testing

python test.py --path=$configpath$ 

For example: python test.py --path=./checkpoints/ImagineGAN/celeba/

SliceGAN

Put the ImagineGAN model in the corresponding directory, for example, checkpoints/SliceGAN/celeba/imagine_g.pth.

• Training

python train.py --path=$configpath$

For example: python train.py --path=./checkpoints/SliceGAN/celeba/

• Testing

python test.py --path=$configpath$ 

For example: python test.py --path=./checkpoints/SliceGAN/celeba/

Citing

@inproceedings{guo2020spiralnet,
author = {Guo, Dongsheng and Liu, Hongzhi and Zhao, Haoru and Cheng, Yunhao and Song, Qingwei and Gu, Zhaorui and Zheng, Haiyong and Zheng, Bing},
title = {Spiral Generative Network for Image Extrapolation},
booktitle = {The European Conference on Computer Vision (ECCV)},
pages={701--717},
year = {2020}
}