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 2521–2530 of 3874 papers

TitleStatusHype
SRDiff: Single Image Super-Resolution with Diffusion Probabilistic ModelsCode1
NTIRE 2021 Challenge on Video Super-Resolution—0
BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and AlignmentCode3
Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation Models—0
Intentional Deep Overfit Learning (IDOL): A Novel Deep Learning Strategy for Adaptive Radiation Therapy—0
SRWarp: Generalized Image Super-Resolution under Arbitrary TransformationCode1
Temporal Modulation Network for Controllable Space-Time Video Super-ResolutionCode1
Photothermal-SR-Net: A Customized Deep Unfolding Neural Network for Photothermal Super Resolution Imaging—0
A Two-Stage Attentive Network for Single Image Super-ResolutionCode1
TWIST-GAN: Towards Wavelet Transform and Transferred GAN for Spatio-Temporal Single Image Super Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified