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 1351–1360 of 3874 papers

TitleStatusHype
Modeling Continuous Spatial-temporal Dynamics of Turbulent Flow with Test-time Refinement—0
TINQ: Temporal Inconsistency Guided Blind Video Quality AssessmentCode0
WaveDiffUR: A diffusion SDE-based solver for ultra magnification super-resolution in remote sensing images—0
Joint Multitarget Detection and Tracking with mmWave Radar—0
Foundation Model for Lossy Compression of Spatiotemporal Scientific Data—0
Uncertainty Estimation for Super-Resolution using ESRGAN—0
Flowing from Words to Pixels: A Framework for Cross-Modality Evolution—0
Learning of Patch-Based Smooth-Plus-Sparse Models for Image ReconstructionCode0
Block-Based Multi-Scale Image Rescaling—0
Sequence Matters: Harnessing Video Models in 3D Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified