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See some recent Announcements here (https://lllyasviel.github.io/Style2PaintsResearch/0615).
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And some previous announcements here (https://lllyasviel.github.io/Style2PaintsResearch/0109).
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Style2Paints will be renamed into "SEPA" before 2022. The name "SEPA" is a short version of "StylE2PAints".
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We are actively developing SEPA (or called style2paints V5).
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If you are interested, we have a twitter account here.
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We have removed the shading functionality from style2paints V4.5 because some packages are incompatiable with the backend engine of V4.5 windows binary release, though the source of V4 is still avaliable. Project SEPA (previously called style2paints v5) has a much better backend engine and the shading functionality will come back in SEPA (style2paints v5).
Currently, we recommend you to use style2paints V4.5 before Project SEPA is ready.
You can directly download the software (windows x64) at:
Google Drive:
https://drive.google.com/open?id=1gmg2wwNIp4qMzxqP12SbcmVAHsLt1iRE
Baidu Drive (百度网盘):
https://pan.baidu.com/s/15xCm1jRVeHipHkiB3n1vzA
QQ Group (QQ群文件):
599929904
You do NOT need to install any complex things like CUDA and python. You can directly download it and then double click it, as if you were playing a normal video game.
Never hesitate to let me know if you have any suggestions or ideas. You may directly send emails to my private address [lvminzhang@acm.org] or [lvminzhang@siggraph.org].
Style2paints V4 is the current best AI driven lineart colorization tool.
Different from previous end-to-end image-to-image translation methods, style2paints V4 is the first system to colorize a lineart in real-life human workflow, and the outputs are layered.
Inputs:
● Linearts
● (with or without) Human hints
● (with or without) Color style reference images
● (with or without) Light location and color
Outputs:
● Automatic color flattening without lines (solid/flat/inherent/固有色/底色 color layer)
● Automatic color flattening with black lines
● Automatic colorization without lines
● Automatic colorization with black lines
● Automatic colorization with colored lines
● Automatic rendering (separated layer)
● Automatic rendered colorization
Style2paints V4 gives you results of the current highest quality. You are able to get separated layers from our system. These layers can be directly used in your painting workflow. Different from all previous AI driven colorization tools, our results are not single 'JPG/PNG' images, and in fact, our results are 'PSD' layers.
User Instruction: https://style2paints.github.io/
And we also have an official Twitter account.
Most human artists are familiar with this workflow:
sketching -> color filling/flattening -> gradients/details adding -> shading
And the corresponding layers are:
lineart layers + flat color layers + gradient layers + shading layers
Style2paints V4 is designed for this standard coloring workflow! In style2paints V4, you can automatically get separated results from each step!
Here we present some results in this ABCD format. Users only need to upload their sketch, select a style, and put a light source.
When the result is achieved immediately without any human color correction, we regard this result as fully automatic result. When the result needs some color correction, human can easily put some color hints on the canvas to guide the AI coloring process. In this case, we regard these results as semi-automatic results. If a result is semi-automatic, but the quantity of human color hint points is smaller than 10, we regard these results as almost automatic result. In this section, about half of the presented results are fully automatic result, and the others are all almost automatic result. Do notice that all the below results can be achieved with less than 15 clicks!
User Instruction: https://style2paints.github.io/
And we also have an official Twitter account.
Thanks a lot to TaiZan. This project could not be achieved without his great help.
All codes are released in Apache-2.0 License.
We preserve all rights on all pretrained deep learning models and binary releases.
Your colorized images are yours, and we do not add any extra lisences to colorized results. Use your colorized images in any commercial or non-commercial cases.
欢迎加入以下qq群，但是不保证一直有空位，如果你一次加群失败，可以多次尝试。
纸片协会：599929904
ACPR 2017:
@Article{ACPR2017ZLM,
author = {LvMin Zhang, Yi Ji and ChunPing Liu},
title = {Style Transfer for Anime Sketches with Enhanced Residual U-net and Auxiliary Classifier GAN},
conference = {Asian Conference on Pattern Recognition (ACPR)},
year = {2017},
}
No Publications.
TOG 2018:
@Article{ACMTOGTSC2018,
author = {LvMin Zhang, Chengze Li, Tien-Tsin Wong, Yi Ji and ChunPing Liu},
title = {Two-stage Sketch Colorization},
journal = {ACM Transactions on Graphics},
year = {2018},
volume = {37},
number = {6},
month = nov,
doi = {https://doi.org/10.1145/3272127.3275090},
}
No Publications.
CVPR2021
@InProceedings{Filling2021zhang,
author={Lvmin Zhang and Chengze Li and Edgar Simo-Serra and Yi Ji and Tien-Tsin Wong and Chunping Liu},
booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
title={User-Guided Line Art Flat Filling with Split Filling Mechanism},
year={2021},
}