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

Showing 721730 of 3874 papers

TitleStatusHype
Enhancing License Plate Super-Resolution: A Layout-Aware and Character-Driven ApproachCode1
Cross-Scale Internal Graph Neural Network for Image Super-ResolutionCode1
DA-MUSIC: Data-Driven DoA Estimation via Deep Augmented MUSIC AlgorithmCode1
Cross-Scope Spatial-Spectral Information Aggregation for Hyperspectral Image Super-ResolutionCode1
Cross-sensor super-resolution of irregularly sampled Sentinel-2 time seriesCode1
Deep Blind Video Super-resolutionCode1
Across Scales & Across Dimensions: Temporal Super-Resolution using Deep Internal LearningCode1
Cross-View Hierarchy Network for Stereo Image Super-ResolutionCode1
Image Super-Resolution with Text Prompt DiffusionCode1
Improving Scene Text Image Super-resolution via Dual Prior Modulation NetworkCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41Unverified