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
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
Boosting Single Image Super-Resolution via Partial Channel ShiftingCode1
Self-Supervised Burst Super-Resolution—0
Lightweight Image Super-Resolution with Superpixel Token InteractionCode1
Decomposition-Based Variational Network for Multi-Contrast MRI Super-Resolution and ReconstructionCode1
MSRA-SR: Image Super-resolution Transformer with Multi-scale Shared Representation Acquisition—0
Fingerprinting Deep Image Restoration Models—0
Multi-Frequency Representation Enhancement with Privilege Information for Video Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified