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---
license: mit
tags:
- image-segmentation
- background-removal
- anime
pretty_name: ToonOut
datasets:
- joelseytre/toonout
base_model:
- ZhengPeng7/BiRefNet
pipeline_tag: image-segmentation
---
# ToonOut Model Weights
Please check out:
- **our repository:** https://github.com/MatteoKartoon/BiRefNet
- **our paper:** [*ToonOut: Fine-tuned Background Removal for Anime Characters*](https://arxiv.org/abs/2509.06839)
- [**the dataset we collected to fine-tune this model**](https://huggingface.co/datasets/joelseytre/toonout/)
## Model Summary
**ToonOut** is a fine-tuned variant of **BiRefNet** specialized for **background removal in anime-style images**.
BiRefNet performs strongly on realistic imagery but struggles with stylized content (e.g., hair wisps, line art, transparency).
Fine-tuned on the [ToonOut Dataset](https://huggingface.co/datasets/joelseytre/ToonOut) (1,228 images), ToonOut delivers a notable boost for anime segmentation:
- **Pixel Accuracy:** 95.3% → **99.5%** (on our test set)
---
## Model Details
- **Architecture:** BiRefNet (fine-tuned)
- **License:** MIT
- **Training data:** [ToonOut Dataset](https://huggingface.co/datasets/joelseytre/ToonOut) (CC-BY 4.0)
---
## Example usage
Please refer to [the demo notebook](https://github.com/MatteoKartoon/BiRefNet/blob/main/toonout_demo.ipynb) from our GitHub repo.
---
## Citation
If you use ToonOut, please cite:
~~~bibtex
@misc{muratori2025toonout,
title={ToonOut: Fine-tuned Background Removal for Anime Characters},
author={Muratori, Matteo and Seytre, Joël},
year={2025},
eprint={2509.06839},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2509.06839},
doi={10.48550/arXiv.2509.06839}
}
~~~
---
## Authors & Contact
- **Authors:** Matteo Muratori (University of Bologna, Kartoon AI), Joël Seytre (Kartoon AI)
- **Contact:** [email protected], [email protected]
⸻
Project by *Kartoon AI*, powering **toongether**, check us out at [kartoon.ai](kartoon.ai) & [toongether.ai](toongether.ai) |