Deep Sketch-Based Modeling: Tips and Tricks

Contents

• Introduction
• Requirements
• Download Dataset
• Results

Introduction

This repository contains the Pytorch implementation of Deep Sketch-Based Modeling: Tips and Tricks, including binary mask prediction and 3D shape reconstruction.

You can find detailed usage instructions for training and evaluation below.

If you find our code or paper useful, please consider citing

@inproceedings{deepsketch2020,
    title = {Deep Sketch-Based Modeling: Tips and Tricks },
    author = {Yue, Zhong and Yulia, Gryaditskaya and Honggang, Zhang and Yi-Zhe, Song},
    booktitle = {Proceedings of International Conference on 3D Vision (3DV)},
    year = {2020}
}

Requirements

First you have to make sure that you have all dependencies in place. The simplest way to do so, is to use anaconda.

Please refer the README file in each sub-task for detailed instruction.

Download Dataset

Download dataset is easy. Directly run

sh scripts/download_dataset.sh

Results

We identify key differences between sketch and image inputs, driving out important insights and proposing the respective solutions, we show an improved performance of deep image modeling..