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 2471–2480 of 3874 papers

TitleStatusHype
Pixel super-resolved lensless on-chip sensor with scattering multiplexing—0
Self-Organized Residual Blocks for Image Super-Resolution—0
CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed TomographyCode1
SNIPS: Solving Noisy Inverse Problems StochasticallyCode1
Deep Hierarchical Super Resolution for Scientific Data—0
Cascaded Diffusion Models for High Fidelity Image Generation—0
Beyond the Spectrum: Detecting Deepfakes via Re-SynthesisCode1
Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understanding—0
CogView: Mastering Text-to-Image Generation via TransformersCode2
Permutation invariance and uncertainty in multitemporal image super-resolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified