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 2331–2340 of 3874 papers

TitleStatusHype
A Simple Plugin for Transforming Images to Arbitrary Scales—0
Nanoscopic distribution of VAChT and VGLUT3 in striatal cholinergic varicosities suggests colocalization and segregation of the two transporters in synaptic vesicles—0
MuS2: A Real-World Benchmark for Sentinel-2 Multi-Image Super-ResolutionCode0
Imagen Video: High Definition Video Generation with Diffusion Models—0
Low-Resolution Action Recognition for Tiny Actions Challenge—0
Deep Sparse and Low-Rank Prior for Hyperspectral Image DenoisingCode0
Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advances—0
Scaling Laws For Deep Learning Based Image ReconstructionCode0
DELTAR: Depth Estimation from a Light-weight ToF Sensor and RGB Image—0
Effective Invertible Arbitrary Image Rescaling—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified