Faces2Anime
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Faces2Anime: Cartoon Style Transfer in Faces using Generative Adversarial Networks. Masters Thesis 2021 @ NTUST.
Faces2Anime
Cartoon Style Transfer in Faces using GANs
This project is aim to accomplish style transfer from human faces to anime / manga / cartoon styles.
Results
Trained styles
The styles used below are from our training dataset.
Un-trained styles
The styles used below are randomly collected from the internet.
Mean style transference
Mean style
denotes the mean of all texture codes of our training styles.
Texture interpolation
Tx rate = n
tx1 : tx2 = 1-n : n
Structure interpolation
Unfortunately, our model fail to interpolate structures as it can only be applied to texture semantic style transfer.
Stu rate = n
stu1 : stu2 = 1-n : n
Results with removing backgrounds using removebg.
Comparison
- Compared methods
- Lighting preservation
Further Transformation
In-Domain GAN Inversion for Real Image Editing
Zhu et al. 2020. [paper] [github]
Toonify!
Justin Pinkney. 2020. [web]
Datasets
:warning: Warning: All images are only used for research purpose. Prohibited for commercial use.
Training data
- Anime
- Human faces
Testing data
-
Anime
- Images randomly collected from the internet. (Total: 170)
-
Human faces
- Images randomly collected from the internet. (Total: 17)
- Images selected from the FFHQ dataset. (Total: 63)
Acknowledgement
- The related research papers:
- Face cartoonization for pre-processing here.
- The idea of this project is highly inspired from naver-webtoon-faces by bryandlee.
- Our code implementation is based on swapping-autoencoder-pytorch by rosinality.
BibTeX Citation
If you find this work useful for your research, please cite:
< English version >
@mastersthesis{huang2021cartoon,
author={Cheryl Huang},
title={Cartoon Style Transfer in Faces using Generative Adversarial Networks},
school={National Taiwan University of Science and Technology},
year={2021},
note={\url{https://hdl.handle.net/11296/j8jm9n}}
}
< Chinese version >
@mastersthesis{huang2021cartoon,
author={黃竹萱},
title={基於生成對抗網路之臉部卡通風格轉換},
school={國立臺灣科技大學資訊工程研究所},
year={2021},
note={\url{https://hdl.handle.net/11296/j8jm9n}}
}
License
Copyright © 2021 Cheryl Huang. All rights reserved.