Lowlight Enhance Mirnet
MIRNet is a fully convolutional neural network specifically designed for low-light image enhancement tasks, capable of fusing multi-scale contextual information while preserving high-resolution details.
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Release Time : 3/2/2022
Model Overview
This model reconstructs high-quality images from low-light input images through deep learning techniques, applicable in fields such as photography, security surveillance, medical imaging, and remote sensing.
Model Features
Multi-scale feature fusion
Simultaneously captures local and global contextual information through unique architectural design
Detail preservation
Effectively maintains high-frequency details and texture features during enhancement
End-to-end training
Adopts end-to-end training to directly learn the mapping relationship from low-light to normal exposure
Model Capabilities
Low-light image enhancement
Image quality restoration
Detail enhancement
Use Cases
Photography enhancement
Night photography enhancement
Improves photo quality taken by smartphones or cameras under low-light conditions
Visible noise reduction and detail enhancement in comparison
Security surveillance
Surveillance video enhancement
Improves visibility of low-light surveillance footage
Increases accuracy in face and object recognition
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