joelseytre/toonout

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)

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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:

~~~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: 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