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 1131–1140 of 3874 papers

TitleStatusHype
Blind Image Super-resolution with Rich Texture-Aware Codebooks—0
Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-ResolutionCode1
Single-pixel imaging based on deep learning—0
Local Statistics for Generative Image Detection—0
Spectral-based detection of chromatin loops in multiplexed super-resolution FISH data—0
Unpaired MRI Super Resolution with Contrastive Learning—0
A Coordinate Descent Approach to Atomic Norm Denoising—0
Parallel compressive super-resolution imaging with wide field-of-view based on physics enhanced network—0
Auxiliary Features-Guided Super Resolution for Monte Carlo Rendering—0
PTSR: Patch Translator for Image Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified