SkillAgentSearch skills...

SSZ

Code for the paper: Image-to-Voxel Model Translation for 3D Scene Reconstruction and Segmentation

Install / Use

/learn @vlkniaz/SSZ
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

Image-to-Voxel Model Translation for 3D Scene Reconstruction and Segmentation

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

Code for the paper: Image-to-Voxel Model Translation for 3D Scene Reconstruction and Segmentation 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]

<img src="images/200823_SSZ_title.jpg" width="900"/>

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

@InProceedings{Kniaz2020,
author="Kniaz, Vladimir A. and
Knyaz, Vladimir V. and Fabio Remondino and
Artem Bordodymov and Petr Moshkantsev
title={SSZ: Image-to-Voxel Model Translation for 3D Scene Reconstruction and Segmentation},
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
pip install visdom
pip install dominate
  • Clone this repo:
git clone https://github.com/vlkniaz/SSZ

StructureFromGAN train/test

  • Go to the repo directory
cd SSZ
  • Download a SSZ dataset:
bash ./datasets/download_ssz_dataset.sh mini
  • Train a model:
bash scripts/train_ssz.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_ssz.sh

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

Apply a pre-trained model (SSZ)

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

  • For example, if you would like to download SSZ model on the mini dataset,
bash pretrained_models/download_ssz_model.sh SSZ
  • Download the mini datasets
bash ./datasets/download_ssz_dataset.sh mini
  • Then generate the results using
bash scripts/test_ssz_pretrained.sh
  • The test results will be saved to a html file here: ./results/SSZ_pretrained/test_latest/index.html.
View on GitHub
GitHub Stars23
CategoryDevelopment
Updated11mo ago
Forks7

Security Score

82/100

Audited on May 6, 2025

No findings