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 3531–3540 of 3874 papers

TitleStatusHype
Enhancement or Super-Resolution: Learning-based Adaptive Video Streaming with Client-Side Video Processing—0
Event Signal Filtering via Probability Flux Estimation—0
Enhanced Signal Recovery via Sparsity Inducing Image Priors—0
Event-Stream Super Resolution using Sigma-Delta Neural Network—0
Event Stream Super-Resolution via Spatiotemporal Constraint Learning—0
Every Pixel Tells a Story: End-to-End Urdu Newspaper OCR—0
EvIntSR-Net: Event Guided Multiple Latent Frames Reconstruction and Super-Resolution—0
EVRNet: Efficient Video Restoration on Edge Devices—0
Enhanced Image Reconstruction From Quarter Sampling Measurements Using An Adapted Very Deep Super Resolution Network—0
Example-Based Modeling of Facial Texture From Deficient Data—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified