---
library_name: BiRefNet
tags:
- background-removal
- mask-generation
- Image Matting
- pytorch_model_hub_mixin
- model_hub_mixin
repo_url: https://github.com/ZhengPeng7/BiRefNet-portrait
pipeline_tag: image-segmentation
---
Bilateral Reference for High-Resolution Dichotomous Image Segmentation
1 Nankai University 2 Northwestern Polytechnical University 3 National University of Defense Technology 4 Aalto University 5 Shanghai AI Laboratory 6 University of Trento
## This repo holds the official weights of BiRefNet for general matting.
### Training Sets:
+ P3M-10k (except TE-P3M-500-P)
+ [TR-humans](https://huggingface.co/datasets/schirrmacher/humans)
### Validation Sets:
+ TE-P3M-500-P
### Performance:
| Dataset | Method | Smeasure | maxFm | meanEm | MAE | maxEm | meanFm | wFmeasure | adpEm | adpFm | HCE |
| :------: | :------: | :------: | :------: | :------: | :------: | :------: | :------: | :------: | :------: | :------: | :------: |
| TE-P3M-500-P | BiRefNet-portrai--epoch_150 | .983 | .996 | .991 | .006 | .997 | .988 | .990 | .933 | .965 | .000 |
**Check the main BiRefNet model repo for more info and how to use it:**
https://huggingface.co/ZhengPeng7/BiRefNet/blob/main/README.md
**Also check the GitHub repo of BiRefNet for all things you may want:**
https://github.com/ZhengPeng7/BiRefNet
## Acknowledgement:
+ Many thanks to @fal for their generous support on GPU resources for training this BiRefNet for portrait matting.
## Citation
```
@article{zheng2024birefnet,
title={Bilateral Reference for High-Resolution Dichotomous Image Segmentation},
author={Zheng, Peng and Gao, Dehong and Fan, Deng-Ping and Liu, Li and Laaksonen, Jorma and Ouyang, Wanli and Sebe, Nicu},
journal={CAAI Artificial Intelligence Research},
volume = {3},
pages = {9150038},
year={2024}
}
```