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 2391–2400 of 3874 papers

TitleStatusHype
Single-shot structured illumination microscopy—0
Real-Time Super-Resolution System of 4K-Video Based on Deep LearningCode1
Learned super resolution ultrasound for improved breast lesion characterization—0
Effectiveness of State-of-the-Art Super Resolution Algorithms in Surveillance Environment—0
Image restoration quality assessment based on regional differential information entropy—0
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation—0
Deep Learning Based Autonomous Vehicle Super Resolution DOA Estimation for Safety Driving—0
Blind Image Super-Resolution: A Survey and Beyond—0
A comparative study of various Deep Learning techniques for spatio-temporal Super-Resolution reconstruction of Forced Isotropic Turbulent flows—0
A Deep Residual Star Generative Adversarial Network for multi-domain Image Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified