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 1701–1710 of 3874 papers

TitleStatusHype
Blind inverse problems with isolated spikes—0
Detecting disruption of HER2 membrane protein organization in cell membranes with nanoscale precision—0
Blind Image Super-Resolution with Spatial Context Hallucination—0
Blind Image Super-resolution with Rich Texture-Aware Codebooks—0
Analysis and Interpretation of Deep CNN Representations as Perceptual Quality Features—0
Detail-Enhancing Framework for Reference-Based Image Super-Resolution—0
Detailed 3D Human Body Reconstruction from Multi-view Images Combining Voxel Super-Resolution and Learned Implicit Representation—0
Blind Image Super-Resolution via Contrastive Representation Learning—0
Blind Image Super-Resolution: A Survey and Beyond—0
Designing A Composite Dictionary Adaptively From Joint Examples—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified