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  [![arXiv](https://img.shields.io/badge/arXiv-2501.06230-b31b1b.svg)](https://arxiv.org/abs/2501.06230)
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  [![GitHub](https://img.shields.io/badge/GitHub-BEN-black.svg)](https://github.com/PramaLLC/BEN/)
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  [![Website](https://img.shields.io/badge/Website-backgrounderase.net-104233)](https://backgrounderase.net)
 
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  ## Overview
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  BEN (Background Erase Network) introduces a novel approach to foreground segmentation through its innovative Confidence Guided Matting (CGM) pipeline. The architecture employs a refiner network that targets and processes pixels where the base model exhibits lower confidence levels, resulting in more precise and reliable matting results.
 
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  [![arXiv](https://img.shields.io/badge/arXiv-2501.06230-b31b1b.svg)](https://arxiv.org/abs/2501.06230)
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  [![GitHub](https://img.shields.io/badge/GitHub-BEN-black.svg)](https://github.com/PramaLLC/BEN/)
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  [![Website](https://img.shields.io/badge/Website-backgrounderase.net-104233)](https://backgrounderase.net)
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+ [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/ben-using-confidence-guided-matting-for/dichotomous-image-segmentation-on-dis-vd)](https://paperswithcode.com/sota/dichotomous-image-segmentation-on-dis-vd?p=ben-using-confidence-guided-matting-for)
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  ## Overview
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  BEN (Background Erase Network) introduces a novel approach to foreground segmentation through its innovative Confidence Guided Matting (CGM) pipeline. The architecture employs a refiner network that targets and processes pixels where the base model exhibits lower confidence levels, resulting in more precise and reliable matting results.