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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1441–1450 of 3874 papers

TitleStatusHype
Joint Maximum Purity Forest with Application to Image Super-ResolutionCode0
IterInv: Iterative Inversion for Pixel-Level T2I ModelsCode0
ELSR: Extreme Low-Power Super Resolution Network For Mobile DevicesCode0
Joint High Dynamic Range Imaging and Super-Resolution from a Single ImageCode0
Adversarial Feedback LoopCode0
JSI-GAN: GAN-Based Joint Super-Resolution and Inverse Tone-Mapping with Pixel-Wise Task-Specific Filters for UHD HDR VideoCode0
Multi Scale Identity-Preserving Image-to-Image Translation Network for Low-Resolution Face RecognitionCode0
AnyTSR: Any-Scale Thermal Super-Resolution for UAVCode0
Is Autoencoder Truly Applicable for 3D CT Super-Resolution?Code0
Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified