BiRefNet_512x512 / README.md
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metadata
library_name: birefnet
tags:
  - background-removal
  - mask-generation
  - Dichotomous Image Segmentation
  - Camouflaged Object Detection
  - Salient Object Detection
  - pytorch_model_hub_mixin
  - model_hub_mixin
repo_url: https://github.com/ZhengPeng7/BiRefNet
pipeline_tag: image-segmentation
license: mit

This BiRefNet was trained with images in 512x512 for higher 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}
}