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 231–240 of 3874 papers

TitleStatusHype
HSRMamba: Contextual Spatial-Spectral State Space Model for Single Image Hyperspectral Super-ResolutionCode1
BF-STVSR: B-Splines and Fourier-Best Friends for High Fidelity Spatial-Temporal Video Super-ResolutionCode1
NeurOp-Diff:Continuous Remote Sensing Image Super-Resolution via Neural Operator DiffusionCode1
StructSR: Refuse Spurious Details in Real-World Image Super-ResolutionCode1
BF-STVSR: B-Splines and Fourier---Best Friends for High Fidelity Spatial-Temporal Video Super-ResolutionCode1
Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual ApproximatorsCode1
VolFormer: Explore More Comprehensive Cube Interaction for Hyperspectral Image Restoration and BeyondCode1
Zero-Shot Image Restoration Using Few-Step Guidance of Consistency Models (and Beyond)Code1
Diffusion Prior Interpolation for Flexibility Real-World Face Super-ResolutionCode1
Solving Inverse Problems via Diffusion Optimal ControlCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified