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 451–460 of 3874 papers

TitleStatusHype
CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed TomographyCode1
Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual ApproximatorsCode1
Beyond the Spectrum: Detecting Deepfakes via Re-SynthesisCode1
BF-STVSR: B-Splines and Fourier-Best Friends for High Fidelity Spatial-Temporal Video Super-ResolutionCode1
Conditional Hyper-Network for Blind Super-Resolution with Multiple DegradationsCode1
Adaptive Semantic-Enhanced Denoising Diffusion Probabilistic Model for Remote Sensing Image Super-ResolutionCode1
AeroRIT: A New Scene for Hyperspectral Image AnalysisCode1
Conditional Simulation Using Diffusion Schrödinger BridgesCode1
Accelerating the Super-Resolution Convolutional Neural NetworkCode1
Consistent Direct Time-of-Flight Video Depth Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified