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 1801–1810 of 3874 papers

TitleStatusHype
Multi-scale Attention Network for Single Image Super-ResolutionCode1
DELTAR: Depth Estimation from a Light-weight ToF Sensor and RGB Image—0
SuperYOLO: Super Resolution Assisted Object Detection in Multimodal Remote Sensing ImageryCode2
Scaling Laws For Deep Learning Based Image ReconstructionCode0
Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advances—0
Deep generative model super-resolves spatially correlated multiregional climate data—0
A heterogeneous group CNN for image super-resolutionCode1
Effective Invertible Arbitrary Image Rescaling—0
Real-RawVSR: Real-World Raw Video Super-Resolution with a Benchmark DatasetCode1
Face Super-Resolution Using Stochastic Differential EquationsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified