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 271–280 of 3874 papers

TitleStatusHype
Catch-A-Waveform: Learning to Generate Audio from a Single Short ExampleCode1
DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-ResolutionCode1
CABM: Content-Aware Bit Mapping for Single Image Super-Resolution Network with Large InputCode1
Deep Random Projector: Accelerated Deep Image PriorCode1
CADyQ: Content-Aware Dynamic Quantization for Image Super-ResolutionCode1
C3-STISR: Scene Text Image Super-resolution with Triple CluesCode1
Deep Posterior Distribution-based Embedding for Hyperspectral Image Super-resolutionCode1
Deep Reparametrization of Multi-Frame Super-Resolution and DenoisingCode1
Deep Semantic Statistics Matching (D2SM) Denoising NetworkCode1
Burstormer: Burst Image Restoration and Enhancement TransformerCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified