| { | |
| "bomFormat": "CycloneDX", | |
| "specVersion": "1.6", | |
| "serialNumber": "urn:uuid:de0e0092-ebc9-47bd-a87c-e9c6fa4bc604", | |
| "version": 1, | |
| "metadata": { | |
| "timestamp": "2025-10-23T16:22:55.869800+00:00", | |
| "component": { | |
| "type": "machine-learning-model", | |
| "bom-ref": "PramaLLC/BEN2-4905de38-3fae-5f7c-8678-e3aa26a22745", | |
| "licenses": [ | |
| { | |
| "license": { | |
| "id": "MIT", | |
| "url": "https://spdx.org/licenses/MIT.html" | |
| } | |
| } | |
| ], | |
| "externalReferences": [ | |
| { | |
| "url": "https://huggingface.co/PramaLLC/BEN2", | |
| "type": "documentation" | |
| } | |
| ], | |
| "modelCard": { | |
| "modelParameters": { | |
| "datasets": [], | |
| "task": "image-segmentation", | |
| "modelArchitecture": "PramaBEN_Base" | |
| }, | |
| "properties": [ | |
| { | |
| "name": "library_name", | |
| "value": "ben2" | |
| } | |
| ] | |
| }, | |
| "name": "PramaLLC/BEN2", | |
| "authors": [ | |
| { | |
| "name": "PramaLLC" | |
| } | |
| ], | |
| "description": "## Overview\nBEN2 (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. This model is built on BEN:\n[](https://paperswithcode.com/sota/dichotomous-image-segmentation-on-dis-vd?p=ben-using-confidence-guided-matting-for)\n\n\n\n", | |
| "tags": [ | |
| "ben2", | |
| "onnx", | |
| "safetensors", | |
| "BEN2", | |
| "background-remove", | |
| "mask-generation", | |
| "Dichotomous image segmentation", | |
| "background remove", | |
| "foreground", | |
| "background", | |
| "remove background", | |
| "pytorch", | |
| "model_hub_mixin", | |
| "pytorch_model_hub_mixin", | |
| "background removal", | |
| "background-removal", | |
| "image-segmentation", | |
| "arxiv:2501.06230", | |
| "license:mit", | |
| "region:us" | |
| ] | |
| } | |
| }, | |
| "components": [] | |
| } |