We provide Pytorch implementation for sRender (i.e. sketch render).
Reference:
Shang, Meimei, Fei Gao *, Xiang Li, Jingjie Zhu, and Lingna Dai. "Bridging Unpaired Facial Photos And Sketches By Line-drawings." In ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2010-2014. IEEE, 6-11 June 2021.
[paper@IEEE] [paper@arXiv] [project@github]
left: croquis style; right: charcoal style
(a)Sketches ; (b)Generated Line-drawings ; (c)Synthesized Sketches
left: croquis style; right: charcoal style
(a)Photos ; (b)Generated Line-drawings ; (c)Synthesized Sketches
- Croquis sketches generated by our sRender and unpaired I2I translation methods
charcoal_stylefor systhesising charcoal style images,it contains sRender w/o Lstr for model without stroke_loss and sRender for model with stroke_loss correspodinglycroquis_stylefor systhesising croquis style images,it contains sRenderPix2Pix, sRender w/o Lstr and sRender- download dataset gray for charcol_style, binary for croquis_style
- download pretrain model and put them in ./checkpoints for test
- for model with stroke_loss, you should download stroke_model and specify model root in ./models/pix2pixHD_model for net_c.load_state_dict
- you can modify options/base_option to specify --dataroot, then run train.py or test.py
- Gray line-drawings for charcol_style from GooleDrive
- Binary line-drawings for croquis_style from GooleDrive
- charcoal_style from GooleDrive
- croquis_style from GooleDrive
- Our synthesis result for croquis and charcoal style can be downloaded from Goole Drive
bib
@inproceedings{shang2021bridging,
title={Bridging Unpaired Facial Photos And Sketches By Line-drawings},
author={Shang, Meimei and Gao, Fei and Li, Xiang and Zhu, Jingjie and Dai, Lingna},
booktitle={ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={2010--2014},
year={2021},
organization={IEEE}
}- Our code is inspired by the AiSketcher repository and the NVIDIA/pix2pixHD repository.