ToonOut: Fine-tuned Background-Removal for Anime Characters

Fuente: arXiv
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Autori principali: Muratori, Matteo, Seytre, Joël
Natura: Preprint
Pubblicazione: 2025
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author Muratori, Matteo
Seytre, Joël
author_facet Muratori, Matteo
Seytre, Joël
contents While state-of-the-art background removal models excel at realistic imagery, they frequently underperform in specialized domains such as anime-style content, where complex features like hair and transparency present unique challenges. To address this limitation, we collected and annotated a custom dataset of 1,228 high-quality anime images of characters and objects, and fine-tuned the open-sourced BiRefNet model on this dataset. This resulted in marked improvements in background removal accuracy for anime-style images, increasing from 95.3% to 99.5% for our newly introduced Pixel Accuracy metric. We are open-sourcing the code, the fine-tuned model weights, as well as the dataset at: https://github.com/MatteoKartoon/BiRefNet.
format Preprint
id arxiv_https___arxiv_org_abs_2509_06839
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle ToonOut: Fine-tuned Background-Removal for Anime Characters
Muratori, Matteo
Seytre, Joël
Computer Vision and Pattern Recognition
Machine Learning
While state-of-the-art background removal models excel at realistic imagery, they frequently underperform in specialized domains such as anime-style content, where complex features like hair and transparency present unique challenges. To address this limitation, we collected and annotated a custom dataset of 1,228 high-quality anime images of characters and objects, and fine-tuned the open-sourced BiRefNet model on this dataset. This resulted in marked improvements in background removal accuracy for anime-style images, increasing from 95.3% to 99.5% for our newly introduced Pixel Accuracy metric. We are open-sourcing the code, the fine-tuned model weights, as well as the dataset at: https://github.com/MatteoKartoon/BiRefNet.
title ToonOut: Fine-tuned Background-Removal for Anime Characters
topic Computer Vision and Pattern Recognition
Machine Learning
url https://arxiv.org/abs/2509.06839