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Birefnet Portrait
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Birefnet Portrait

Developed by ZhengPeng7
BiRefNet is a deep learning model for high-resolution binary image segmentation, particularly skilled in background removal and mask generation.
Image Segmentation
Safetensors
#High-resolution image segmentation#Bilateral reference network#Portrait matting
Downloads 15.78k
Release Time : 5/13/2024

Model Overview

BiRefNet achieves efficient image segmentation through a bilateral reference mechanism, primarily used for image matting tasks, capable of generating high-quality masks.

Model Features

High-resolution processing
Capable of handling high-resolution images while preserving detail integrity.
Bilateral reference mechanism
Employs a bilateral reference strategy to enhance segmentation accuracy.
Efficient matting
Excels in background removal and mask generation tasks.

Model Capabilities

Image segmentation
Background removal
Mask generation
Image matting

Use Cases

Image processing
Portrait matting
Precisely separates portraits from complex backgrounds
Achieves an S-measure of 0.983 on the TE-P3M-500-P dataset
Product image processing
Generates transparent backgrounds for e-commerce product images
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