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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1801–1825 of 3874 papers

TitleStatusHype
DeepRemaster: Temporal Source-Reference Attention Networks for Comprehensive Video Enhancement—0
Joint Range-Velocity-Azimuth Estimation for OFDM-Based Integrated Sensing and Communication—0
A Frequency Domain Constraint for Synthetic and Real X-ray Image Super Resolution—0
Joint Semi-supervised 3D Super-Resolution and Segmentation with Mixed Adversarial Gaussian Domain Adaptation—0
Image Super-Resolution With Deep Variational Autoencoders—0
Image Super-Resolution with Guarantees via Conformalized Generative Models—0
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution—0
Fast and selective super-resolution ultrasound in vivo with sono-switchable nanodroplets—0
Image-to-image domain adaptation for vehicle re-identification—0
Continuous Space-Time Video Super-Resolution Utilizing Long-Range Temporal Information—0
Image Transformer—0
IMDeception: Grouped Information Distilling Super-Resolution Network—0
A self-adapting super-resolution structures framework for automatic design of GAN—0
Fast and Light-Weight Network for Single Frame Structured Illumination Microscopy Super-Resolution—0
Continuous Sign Language Recognition via Temporal Super-Resolution Network—0
Joint Multitarget Detection and Tracking with mmWave Radar—0
A Framework for Super-Resolution of Scalable Video via Sparse Reconstruction of Residual Frames—0
A comprehensive review on Plant Leaf Disease detection using Deep learning—0
Fast and Accurate Image Upscaling With Super-Resolution Forests—0
Joint Multiple FMCW Chirp Sequence Processing for Velocity Estimation and Ambiguity Resolving—0
Joint OAM Radar-Communication Systems: Target Recognition and Beam Optimization—0
Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI—0
Joint Super-Resolution and Rectification for Solar Cell Inspection—0
A Scale-Arbitrary Image Super-Resolution Network Using Frequency-domain Information—0
AsConvSR: Fast and Lightweight Super-Resolution Network with Assembled Convolutions—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified