ToonOut Model Weights
Please check out:
- our repository: https://github.com/MatteoKartoon/BiRefNet
- our paper: ToonOut: Fine-tuned Background Removal for Anime Characters
- the dataset we collected to fine-tune this model
- Replicate endpoint to try out the model (courtesy of J. H. Cho @sprited)
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 (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 (CC-BY 4.0)
Example usage
Please refer to the demo notebook from our GitHub repo.
Citation
If you use ToonOut, please cite:
@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: joel@kartoon.ai, matteo.muratori9@studio.unibo.it
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Project by Kartoon AI, powering toongether, check us out at kartoon.ai & toongether.ai