LayerD BiRefNet is the matting module in the LayerD graphic design image layer decomposition framework, specifically designed to accurately extract foreground objects from graphic design images. This model is based on the BiRefNet architecture and performs excellently in layer decomposition tasks.

Computer VisionSafetensorsEnglish

BiRefNet is a deep learning model for binary image segmentation, specifically designed for background removal tasks. This model has been converted to the GGUF format and can perform lightweight inference on consumer-grade hardware through vision.cpp, enabling efficient image segmentation processing.

Computer VisionGguf

BiRefNet is a model for high-resolution binary image segmentation, particularly skilled in anime segmentation and background removal tasks.

Computer VisionTransformers

BiRefNet is a bilateral reference framework model for high-resolution binary image segmentation, focusing on tasks such as background removal and mask generation, supporting image processing at resolutions of 2048x2048 and above.

Computer VisionSafetensors

BiRefNet is an advanced model for high-resolution binary image segmentation, particularly adept at background removal and mask generation tasks.

Computer VisionTransformers

BiRefNet is a high-resolution binary image segmentation model based on bilateral reference, specifically designed for high-resolution transparent image matting.

Computer VisionSafetensors

BiRefNet is a deep learning model for high-resolution binary image segmentation, focusing on background removal and mask generation tasks.

Computer VisionSafetensors

BiRefNet is a bilateral reference framework model for high-resolution binary image segmentation, focusing on background removal and mask generation tasks.

Computer VisionSafetensors

BiRefNet is a deep learning model for high-resolution binary image segmentation, capable of precisely separating foreground objects from the background.

Computer VisionSafetensors

BiRefNet is a deep learning model for high-resolution binary image segmentation, achieving precise image segmentation through a bilateral reference mechanism.

Computer VisionSafetensors

BiRefNet is a deep learning model for high-resolution binary image segmentation, achieving precise image segmentation through a bilateral reference mechanism.

Computer VisionSafetensors

BiRefNet is a high-resolution binary image segmentation model based on bilateral reference, focusing on background removal and mask generation tasks.

Computer VisionSafetensors

A bilateral reference framework for high-resolution binary image segmentation, focusing on background removal and mask generation tasks

Computer VisionSafetensors

BiRefNet is a high-resolution binary image segmentation model that employs a bilateral reference framework and delivers excellent performance across multiple image segmentation tasks.

Computer VisionSafetensors

BiRefNet is a high-resolution binary image segmentation model based on bilateral reference, specifically designed for background removal and mask generation tasks.

Computer VisionSafetensors

High-resolution binary image segmentation model based on bilateral reference, focusing on salient object detection and background removal tasks

Computer VisionSafetensors

BiRefNet is a deep learning model for high-resolution binary image segmentation, focusing on background removal and mask generation tasks.

Computer VisionSafetensors

A bilateral reference framework for high-resolution binary image segmentation, focusing on background removal and mask generation tasks

Computer VisionSafetensors

BiRefNet is a high-resolution binary image segmentation model that employs a bilateral reference framework and demonstrates excellent performance across multiple image segmentation tasks.

Computer VisionSafetensors

BiRefNet is a deep learning model for high-resolution binary image segmentation, which achieves accurate image segmentation through a bilateral reference network.

Computer VisionTransformers