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 1591–1600 of 3874 papers

TitleStatusHype
A statistically constrained internal method for single image super-resolution—0
A Convex Approach for Image Hallucination—0
Identity-Preserving Pose-Robust Face Hallucination Through Face Subspace Prior—0
Creating Realistic Anterior Segment Optical Coherence Tomography Images using Generative Adversarial Networks—0
A Statistical Learning Perspective on Semi-dual Adversarial Neural Optimal Transport Solvers—0
Fidelity-Naturalness Evaluation of Single Image Super Resolution—0
Guided Frequency Loss for Image Restoration—0
Guided Image Restoration via Simultaneous Feature and Image Guided Fusion—0
FFTLasso: Large-Scale LASSO in the Fourier Domain—0
IEGAN: Multi-purpose Perceptual Quality Image Enhancement Using Generative Adversarial Network—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified