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ZhengPeng7/BiRefNet_512x512

🤗 Hugging Face sourceimage-segmentationmit221M params444 MBsafetensors✓ 1 checksumupdated today
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This BiRefNet was trained with images in 512x512 for faster and more accurate lower resolution inference.

Performance:

All tested in FP16 mode.

Dataset Method Resolution maxFm wFmeasure MAE Smeasure meanEm HCE maxEm meanFm adpEm adpFm mBA maxBIoU meanBIoU
DIS-VD BiRefNet_512x512-epoch_216 512x512 .879 .840 .040 .888 .931 1526 .941 .864 .938 .857 .732 .747 .726
DIS-VD BiRefNet-general-epoch_244 512x512 .834 .789 .050 .860 .891 1589 .905 .817 .902 .816 .708 .698 .669
DIS-VD BiRefNet_HR-general-epoch_130 512x512 .540 .409 .112 .634 .565 1647 .682 .428 .690 .576 .585 .384 .309

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                     
DIS-Sample_1 DIS-Sample_2

This repo is the official implementation of "Bilateral Reference for High-Resolution Dichotomous Image Segmentation" (CAAI AIR 2024).

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}
}