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 476–500 of 3874 papers

TitleStatusHype
SVCNet: Scribble-based Video Colorization Network with Temporal AggregationCode1
Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image RestorationCode1
LSwinSR: UAV Imagery Super-Resolution based on Linear Swin TransformerCode1
Learning Data-Driven Vector-Quantized Degradation Model for Animation Video Super-ResolutionCode1
Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection StrategyCode1
Iterative Soft Shrinkage Learning for Efficient Image Super-ResolutionCode1
DeblurSR: Event-Based Motion Deblurring Under the Spiking RepresentationCode1
Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data OverfittingCode1
ResDiff: Combining CNN and Diffusion Model for Image Super-ResolutionCode1
Improving 3D Imaging with Pre-Trained Perpendicular 2D Diffusion ModelsCode1
Super-Resolution Information Enhancement For Crowd CountingCode1
Recursive Generalization Transformer for Image Super-ResolutionCode1
Generative AI for Rapid Diffusion MRI with Improved Image Quality, Reliability and GeneralizabilityCode1
LMR: A Large-Scale Multi-Reference Dataset for Reference-based Super-ResolutionCode1
Local Implicit Normalizing Flow for Arbitrary-Scale Image Super-ResolutionCode1
Learning multi-scale local conditional probability models of imagesCode1
BrainBERT: Self-supervised representation learning for intracranial recordingsCode1
Learning to Super-Resolve Blurry Images with EventsCode1
Joint Learning of Blind Super-Resolution and Crack Segmentation for Realistic Degraded ImagesCode1
A residual dense vision transformer for medical image super-resolution with segmentation-based perceptual loss fine-tuningCode1
Improving Scene Text Image Super-resolution via Dual Prior Modulation NetworkCode1
LIT-Former: Linking In-plane and Through-plane Transformers for Simultaneous CT Image Denoising and DeblurringCode1
RecFNO: a resolution-invariant flow and heat field reconstruction method from sparse observations via Fourier neural operatorCode1
Guided Depth Map Super-resolution: A SurveyCode1
Learning Non-Local Spatial-Angular Correlation for Light Field Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified