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 241–250 of 3874 papers

TitleStatusHype
Analysis and evaluation of Deep Learning based Super-Resolution algorithms to improve performance in Low-Resolution Face RecognitionCode1
Physics Driven Deep Retinex Fusion for Adaptive Infrared and Visible Image FusionCode1
Burstormer: Burst Image Restoration and Enhancement TransformerCode1
CNN-generated images are surprisingly easy to spot... for nowCode1
Accelerating Diffusion Models for Inverse Problems through Shortcut SamplingCode1
Burst Super-Resolution with Diffusion Models for Improving Perceptual QualityCode1
Collapsible Linear Blocks for Super-Efficient Super ResolutionCode1
Combining Attention Module and Pixel Shuffle for License Plate Super-ResolutionCode1
Component Divide-and-Conquer for Real-World Image Super-ResolutionCode1
Burst Image Restoration and EnhancementCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified