Anime Face Generating Using Deep Learning

Shaik Muskan Begum, Desam Yashoda, P. Raga Chandrika, Veena Madhuri, Sura Sravani

2025

Abstract

In recent years, the rise of deep learning technologies has greatly enhanced the capabilities of generating realistic and artistic images. One area that has gained significant attention is the automatic generation of anime faces. These images, characterized by distinct features such as large eyes, exaggerated facial expressions, and vibrant hair colors, have seen widespread use in both entertainment and art. The task of generating such faces requires an effective combination of deep learning techniques, including Convolutional Neural Networks (CNNs), Generative Adversarial Networks (GANs), and Variational Autoencoders (VAEs). This paper proposes a novel approach for generating anime faces using deep learning methods. Our model leverages a GAN architecture, where the generator creates high-quality anime faces, and the discriminator ensures that these faces appear realistic and true to the style. To train this model, we use a large dataset of labeled anime face images, ensuring diversity in terms of facial expressions, hair styles, and other unique anime traits. The dataset is preprocessed to extract important facial features, which allows the model to focus on learning the abstract characteristics of anime faces, such as the stylized proportions and exaggerated features.

Paper Citation

in Harvard Style

Begum S., Yashoda D., Chandrika P., Madhuri V. and Sravani S. (2025). Anime Face Generating Using Deep Learning. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 202-207. DOI: 10.5220/0013910400004919

in Bibtex Style

@conference{icrdicct`2525,
author={Shaik Begum and Desam Yashoda and P. Chandrika and Veena Madhuri and Sura Sravani},
title={Anime Face Generating Using Deep Learning},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={202-207},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013910400004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Anime Face Generating Using Deep Learning
SN - 978-989-758-777-1
AU - Begum S.
AU - Yashoda D.
AU - Chandrika P.
AU - Madhuri V.
AU - Sravani S.
PY - 2025
SP - 202
EP - 207
DO - 10.5220/0013910400004919
PB - SciTePress