dualFace: Two-Stage Drawing Guidance for Freehand Portrait Sketching (CVMJ)
We provide python implementations for our CVM 2021 paper "dualFace:Two-Stage Drawing Guidance for Freehand Portrait Sketching". This project provide sketch support for artistic portrait drawings with a two-stage framework. [arXiv][PDF][Project][Video]
bat
call conda remove -n py36df
call conda create -n py36df python=3.6
call conda activate py36df
call conda install pytorch==1.3.1 -c pytorch
pip install cmake
pip install -r requirements.txt
cd sse
sse.exe "-i index_file -v vocabulary -f filelist -n 8"
call conda activate py36df
python demo.py
Our code has depended on the following opensource codes.
Please contact xie@jaist.ac.jp for any comments or requests.
If you use this code for your research, please cite our paper.
@article{dualface2021,
author = {Zhengyu Huang and
Yichen Peng and
Tomohiro Hibino and
Chunqi Zhao and
Haoran Xie and
Tsukasa Fukusato and
Kazunori Miyata},
title = {dualFace: Two-Stage Drawing Guidance for Freehand Portrait Sketching},
journal = {Computational Visual Media},
volume = {8},
pages = {63–77},
year = {2022},
url = {https://doi.org/10.1007/s41095-021-0227-7}
}