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 2201–2210 of 3874 papers

TitleStatusHype
Super-resolution with Binary Priors: Theory and Algorithms—0
Surveillance Face Anti-spoofing—0
In-situ monitoring additive manufacturing process with AI edge computing—0
Spectral Bandwidth Recovery of Optical Coherence Tomography Images using Deep Learning—0
Correspondence Transformers With Asymmetric Feature Learning and Matching Flow Super-ResolutionCode0
PIRNet: Privacy-Preserving Image Restoration Network via Wavelet Lifting—0
Kernel Aware Resampler—0
MSRA-SR: Image Super-resolution Transformer with Multi-scale Shared Representation Acquisition—0
RefSR-NeRF: Towards High Fidelity and Super Resolution View SynthesisCode0
Content-Aware Local GAN for Photo-Realistic Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified