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 1571–1580 of 3874 papers

TitleStatusHype
Camera Lens Super-ResolutionCode0
Image Formation Model Guided Deep Image Super-ResolutionCode0
Decoupling Fine Detail and Global Geometry for Compressed Depth Map Super-ResolutionCode0
Image Restoration Using Convolutional Auto-encoders with Symmetric Skip ConnectionsCode0
I^3Net: Inter-Intra-slice Interpolation Network for Medical Slice SynthesisCode0
IG-CFAT: An Improved GAN-Based Framework for Effectively Exploiting Transformers in Real-World Image Super-ResolutionCode0
Dual-Stream Fusion Network for Spatiotemporal Video Super-ResolutionCode0
Hyperspectral Super-Resolution via Global-Local Low-Rank Matrix EstimationCode0
A New Multi-Picture Architecture for Learned Video Deinterlacing and Demosaicing with Parallel Deformable Convolution and Self-Attention BlocksCode0
Image Restoration Using Deep Regulated Convolutional NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified