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 2521–2530 of 3874 papers

TitleStatusHype
Semi-Supervised Super-Resolution—0
Sensing User's Channel and Location with Terahertz Extra-Large Reconfigurable Intelligent Surface under Hybrid-Field Beam Squint Effect—0
Separation-Free Spectral Super-Resolution via Convex Optimization—0
Separation-Free Super-Resolution from Compressed Measurements is Possible: an Orthonormal Atomic Norm Minimization Approach—0
Sequence Matters: Harnessing Video Models in 3D Super-Resolution—0
Seven ways to improve example-based single image super resolution—0
Sewer Image Super-Resolution with Depth Priors and Its Lightweight Network—0
Sex-Classification from Cell-Phones Periocular Iris Images—0
SGDFormer: One-stage Transformer-based Architecture for Cross-Spectral Stereo Image Guided Denoising—0
ShipSRDet: An End-to-End Remote Sensing Ship Detector Using Super-Resolved Feature Representation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified