SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

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Showing 1541–1550 of 3874 papers

TitleStatusHype
Fingerprinting Deep Image Restoration Models—0
Generative AI in Vision: A Survey on Models, Metrics and Applications—0
A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery—0
Fine-tuned Generative Adversarial Network-based Model for Medical Image Super-Resolution—0
A Generative Model for Generic Light Field Reconstruction—0
Generative Powers of Ten—0
A Coordinate Descent Approach to Atomic Norm Denoising—0
Generator From Edges: Reconstruction of Facial Images—0
Generic 3D Convolutional Fusion for image restoration—0
2D Neural Fields with Learned Discontinuities—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified