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 1601–1610 of 3874 papers

TitleStatusHype
Gull: A Generative Multifunctional Audio Codec—0
GUN: Gradual Upsampling Network for Single Image Super-Resolution—0
H2-Stereo: High-Speed, High-Resolution Stereoscopic Video System—0
HAAT: Hybrid Attention Aggregation Transformer for Image Super-Resolution—0
Image Enhancement by Recurrently-trained Super-resolution Network—0
Handling Motion Blur in Multi-Frame Super-Resolution—0
Image Neural Field Diffusion Models—0
FFT-Enhanced Low-Complexity Near-Field Super-Resolution Sensing—0
Harnessing Artificial Intelligence To Reduce Phototoxicity in Live Imaging—0
FFEINR: Flow Feature-Enhanced Implicit Neural Representation for Spatio-temporal Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified