

Uniref++
Overview :
UniRef is a unified model for image and video object segmentation. It supports multiple tasks such as Semantic Reference Image Segmentation (RIS), Few-Shot Segmentation (FSS), Semantic Reference Video Object Segmentation (RVOS), and Video Object Segmentation (VOS). The core of UniRef is the UniFusion module, which can efficiently inject various reference information into the basic network. UniRef can be used as a plugin component for basic models like SAM. UniRef provides pre-trained models on multiple benchmark datasets and also offers open-source code for research purposes.
Target Users :
["Object Segmentation","Image Segmentation","Video Segmentation","Few-Shot Learning","Multi-Task Learning"]
Use Cases
Using UniRef for interactive image segmentation
Using UniRef for video object tracking and segmentation
Adding UniRef as a plugin to the basic model for semantic segmentation
Features
Supports multiple object segmentation tasks: RIS, FSS, RVOS, and VOS
UniFusion module efficiently injects reference information
Can be used as a plugin for basic models
Provides pre-trained models
Open-source code
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