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 2831–2840 of 3874 papers

TitleStatusHype
The Domain Transform Solver—0
The End Restraint Method for Mechanically Perturbing Nucleic Acids in silico—0
Medical Image Super-Resolution Using a Generative Adversarial Network—0
Theoretical Perspectives on Deep Learning Methods in Inverse Problems—0
Theory of Generative Deep Learning : Probe Landscape of Empirical Error via Norm Based Capacity Control—0
The Perception-Robustness Tradeoff in Deterministic Image Restoration—0
The Power of Context: How Multimodality Improves Image Super-Resolution—0
ThermalNeRF: Thermal Radiance Fields—0
Thermodynamics-informed super-resolution of scarce temporal dynamics data—0
Thermographic detection of internal defects using 2D photothermal super resolution reconstruction with sequential laser heating—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified