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ZhengPeng7/BiRefNet_lite-matting

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Bilateral Reference for High-Resolution Dichotomous Image Segmentation

Peng Zheng 1,4,5,6,  Dehong Gao 2,  Deng-Ping Fan 1*,  Li Liu 3,  Jorma Laaksonen 4,  Wanli Ouyang 5,  Nicu Sebe 6 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 .978 .996 .990 .003 .996 .987 .989 .962 .980 .000 .825 .934 .888
TE-AM-2k BiRefNet-matting--epoch_100 .970 .995 .989 .003 .996 .986 .987 .985 .990 .000 .830 .937 .876

Check the main BiRefNet_lite model repo for more info and how to use it:
https://huggingface.co/ZhengPeng7/BiRefNet_lite/blob/main/README.md

Also check the GitHub repo of BiRefNet for all things you may want:
https://github.com/ZhengPeng7/BiRefNet

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}
}