🛠️

Tool

Faces2Anime

Name: Faces2Anime
Author: CherylHuang

by CherylHuang gh-tool--cherylhuang--faces2anime

Nexus Index

0.0 Top 18%

S: Semantic 50

A: Authority 0

P: Popularity 0

R: Recency 0

Q: Quality 0

Tech Context

Vital Performance

0 DL / 30D

0.0%

paper | video | slides !./imgs/tx_interpolation.gif !./imgs/tx_interpolation.PNG This project is aim to accomplish style transfer from human faces to anime / manga / cartoon styles. The styles used below are from our training dataset. !./imgs/trained_style.PNG !./imgs/trained_style2.PNG The styles used below are randomly collected from the internet. !./imgs/un-trained_style.PNG !./imgs/un-trained_style2.PNG denotes the mean of all texture codes of our training styles. !./imgs/mean_style_trans...

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Python Lang

Open Source 107 Stars

1.0.0 Version

Alpha Reliability

Tool Information Summary
Entity Passport
Registry ID	gh-tool--cherylhuang--faces2anime
Provider	github

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Cite this tool

Academic & Research Attribution

BibTeX

@misc{gh_tool__cherylhuang__faces2anime,
  author = {CherylHuang},
  title = {Faces2Anime Tool},
  year = {2026},
  howpublished = {\url{https://github.com/CherylHuang/Faces2Anime}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}

APA Style

CherylHuang. (2026). Faces2Anime [Tool]. Free2AITools. https://github.com/CherylHuang/Faces2Anime

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🐙 GitHub Clone

git clone https://github.com/CherylHuang/Faces2Anime

🐍 PIP Install

pip install faces2anime

⚖️ Nexus Index V2.0

Methodology Index Protocol

0.0

TOP 18% SYSTEM IMPACT

Semantic (S) 50

Authority (A) 0

Popularity (P) 0

Recency (R) 0

Quality (Q) 0

💬 Index Insight

FNI V2.0 for Faces2Anime: Semantic (S:50), Authority (A:0), Popularity (P:0), Recency (R:0), Quality (Q:0).

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📋 Specs

Language: Python
License: Open Source
Version: 1.0.0

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Usage documentation not yet indexed for this tool.

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Technical Documentation

Faces2Anime

Cartoon Style Transfer in Faces using GANs

paper | video | slides

./imgs/tx_interpolation.gif ./imgs/tx_interpolation.PNG 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.

./imgs/trained_style.PNG

./imgs/trained_style2.PNG

Un-trained styles

The styles used below are randomly collected from the internet.

./imgs/un-trained_style.PNG

./imgs/un-trained_style2.PNG

Mean style transference

Mean style denotes the mean of all texture codes of our training styles.

./imgs/mean_style_transfer.PNG

Texture interpolation

text

Tx rate = n
tx1 : tx2 = 1-n : n

./imgs/tx_interpolation2.PNG

Structure interpolation

Unfortunately, our model fail to interpolate structures as it can only be applied to texture semantic style transfer.

text

Stu rate = n
stu1 : stu2 = 1-n : n

./imgs/stu_interpolation.PNG

Results with removing backgrounds using removebg.

./imgs/stu_interpolation2.PNG

Comparison

Compared methods
- U-GAT-IT [paper] [web] [github]
- Artbreeder [web]
- neural-style-tf [github]
- deepart io [web]
- Deep Image Analogy [paper] [github]
- FaceBlit [paper] [github]
- Adobe Characterizer [web] [video]
- original SwapAE [paper] [github]
- WCT2 [paper] [github]

./imgs/comparison1.PNG

./imgs/comparison2.PNG

Lighting preservation

./imgs/comparison3.PNG

Further Transformation

In-Domain GAN Inversion for Real Image Editing

Zhu et al. 2020. [paper] [github]

./imgs/further_in-domain.PNG

Toonify!

Justin Pinkney. 2020. [web]

./imgs/further_toonify.PNG

Datasets

:warning: Warning: All images are only used for research purpose. Prohibited for commercial use.

Training data

Anime
- Images randomly collected from WEBTOON. (Total: 22,741; Titles: 128)
- Images generated from StyleGAN2 anime pre-train model. (Total: 300)
Human faces
- Images generated from StyleGAN2 FFHQ pre-train model. (Total: 3,802)
- Celebrity faces selected from the CelebA dataset and randomly collected from the internet. (Total: 1,311)

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:
- Swapping Autoencoder for Deep Image Manipulation [paper] [github]
- Learning to Cartoonize Using White-box Cartoon Representations [paper] [github]
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 >

text

@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 >

text

@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

Social Proof

GitHub Repository

107Stars

6Forks

Repo Issues

🐙 Data Source: GitHub ↗

🔄 Daily sync (03:00 UTC)

AI Summary: Based on GitHub metadata. Not a recommendation.

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🛡️ Tool Transparency Report

Verified data manifest for traceability and transparency.

100% Data Disclosure Active

🆔 Identity & Source

id: gh-tool--cherylhuang--faces2anime
source: github
author: CherylHuang
tags: gandeep-learningpytorchstyle-transferface2cartoonimage-to-image-translationimage-generation

⚙️ Technical Specs

architecture: null
params billions: null
context length: null
pipeline tag: text-to-image

📊 Engagement & Metrics

likes: 0
downloads: 0
github stars: 107

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Cite this tool

🔬Technical Deep Dive

Quick Commands

⚖️ Nexus Index V2.0

💬 Index Insight

Verification Authority

📋 Specs

Technical Documentation

Faces2Anime

Cartoon Style Transfer in Faces using GANs

Results

Trained styles

Un-trained styles

Mean style transference

Texture interpolation

Structure interpolation

Comparison

Further Transformation

In-Domain GAN Inversion for Real Image Editing

Toonify!

Datasets

Training data

Testing data

Acknowledgement

BibTeX Citation

License

Social Proof

🛡️ Tool Transparency Report

🆔 Identity & Source

⚙️ Technical Specs

📊 Engagement & Metrics