---
library_name: BiRefNet
tags:
- background-removal
- mask-generation
- Image Matting
- pytorch_model_hub_mixin
- model_hub_mixin
repo_url: https://github.com/ZhengPeng7/BiRefNet-matting
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-NP)
+ TR-humans
+ AM-2k
+ AIM-500
+ Human-2k (synthesized with BG-20k)
+ Distinctions-646 (synthesized with BG-20k)
+ HIM2K
+ PPM-100
### Validation Sets:
+ TE-P3M-500-NP
### Performance:
| Dataset | Method | Smeasure | maxFm | meanEm | MSE | maxEm | meanFm | wFmeasure | adpEm | adpFm | HCE | mBA | maxBIoU | meanBIoU |
| :------: | :------: | :------: | :------: | :------: | :------: | :------: | :------: | :------: | :------: | :------: | :------: | :------: | :------: | :------: |
| TE-P3M-500-NP | BiRefNet-matting--epoch_100 | .979 | .996 | .988 | .003 | .997 | .986 | .988 | .864 | .885 | .000 | .830 | .940 | .888 |
**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 @freepik for their generous support on GPU resources for training this model!
## 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}
}
```