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 1051–1060 of 3874 papers

TitleStatusHype
An End-to-end Framework For Low-Resolution Remote Sensing Semantic SegmentationCode1
EBSR: Feature Enhanced Burst Super-Resolution With Deformable AlignmentCode1
Real-World Image Super-Resolution by Exclusionary Dual-LearningCode1
Does Diffusion Beat GAN in Image Super Resolution?Code1
Single Image Super-Resolution via CNN Architectures and TV-TV MinimizationCode1
EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-ResolutionCode1
NCAP: Scene Text Image Super-Resolution with Non-CAtegorical PriorCode0
A Deep Journey into Super-resolution: A surveyCode0
Natural and Realistic Single Image Super-Resolution with Explicit Natural Manifold DiscriminationCode0
Near field Acoustic Holography on arbitrary shapes using Convolutional Neural NetworkCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified