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PURE

Developed by nonwhy
PURE is the first framework to employ a Multimodal Large Language Model (MLLM) as the backbone network for solving low-level vision tasks.
Image Enhancement
Safetensors
#MLLM Super-Resolution#Multimodal Image Enhancement#Zero-Shot Learning
Downloads 326
Release Time : 4/9/2025

Model Overview

PURE is an image-to-image model focused on super-resolution tasks, leveraging a Multimodal Large Language Model (MLLM) as the backbone network to enhance performance in low-level vision tasks.

Model Features

Multimodal Large Language Model Backbone
First adoption of MLLM as the backbone network in low-level vision tasks, potentially offering superior feature extraction capabilities.
Super-Resolution Processing
Specialized in image super-resolution tasks, capable of improving image quality and clarity.

Model Capabilities

Image Super-Resolution
Image Quality Enhancement

Use Cases

Image Processing
Image Enhancement
Performs super-resolution processing on low-resolution images to enhance image quality.
Inference: Likely to produce higher-resolution image outputs
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