--- library_name: birefnet tags: - Anime Segmentation - background-removal - mask-generation - Dichotomous Image Segmentation - Salient Object Detection - pytorch_model_hub_mixin - model_hub_mixin - transformers - transformers.js repo_url: https://github.com/ZhengPeng7/BiRefNet pipeline_tag: image-segmentation license: mit ---

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} } ```