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 2911–2920 of 3874 papers

TitleStatusHype
UGPNet: Universal Generative Prior for Image Restoration—0
Ultra-Range Gesture Recognition using a Web-Camera in Human-Robot Interaction—0
UltraVSR: Achieving Ultra-Realistic Video Super-Resolution with Efficient One-Step Diffusion Space—0
Unaligned RGB Guided Hyperspectral Image Super-Resolution with Spatial-Spectral Concordance—0
Uncertainty-Driven Loss for Single Image Super-Resolution—0
Uncertainty Estimation for Super-Resolution using ESRGAN—0
Uncertainty-guided Perturbation for Image Super-Resolution Diffusion Model—0
Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement—0
Uncertainty Quantification via Neural Posterior Principal Components—0
Understanding Deformable Alignment in Video Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified