StructureFromGAN

NOTE: We are preparing the final code for release on GitHub. It will be published by September 20.

Code for the paper: StructureFromGAN: Single Image 3D Model Reconstruction and Photorealistic Texturing This is the PyTorch implementation of the color-to-voxel model translation presented on ECCV 2018.

The code is based on the PyTorch implementation of the pix2pix and CycleGAN.

StructureFromGAN: [Project] [Paper]

If you use this code for your research, please cite:

@InProceedings{Kniaz2020,
author="Kniaz, Vladimir A. and
Knyaz, Vladimir V. and Vladimir Mizginov and
Mark Kozyrev and Petr Moshkantsev
title={StructureFromGAN: Single Image 3D Model Reconstruction and Photorealistic Texturing},
booktitle={{Computer Vision -- ECCV 2020 Workshops",
year="2020}},
publisher={Springer International Publishing},
}

Prerequisites

Linux or macOS
Python 2 or 3
CPU or NVIDIA GPU + CUDA CuDNN

Getting Started

Installation

Install PyTorch and dependencies from http://pytorch.org
Install Torch vision from the source.

git clone https://github.com/pytorch/vision
cd vision
python setup.py install

Install python libraries visdom and dominate.

pip install visdom
pip install dominate

Clone this repo:

git clone https://github.com/vlkniaz/StructureFromGAN

StructureFromGAN train/test

Go to the repo directory

cd SFG

Download a StructureFromGAN dataset:

bash ./datasets/download_sfg_dataset.sh mini

Train a model:

bash scripts/train_sfg.sh

To view training results and loss plots, run python -m visdom.server and click the URL http://localhost:8097. To see more intermediate results, check out ./checkpoints/thermal_gan_rel/web/index.html
Test the model:

bash scripts/test_sfg.sh

The test results will be saved to a html file here: ./results/sfg/test_latest/index.html.

Apply a pre-trained model (SFG)

Download a pre-trained model with ./pretrained_models/download_sfg_model.sh.

For example, if you would like to download SFG model on the mini dataset,

bash pretrained_models/download_sfg_model.sh SFG

Download the mini datasets

bash ./datasets/download_sfg_dataset.sh mini

Then generate the results using

bash scripts/test_sfg_pretrained.sh

The test results will be saved to a html file here: ./results/SFG_pretrained/test_latest/index.html.