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 1376–1400 of 3874 papers

TitleStatusHype
Learning a Single Convolutional Super-Resolution Network for Multiple DegradationsCode0
Learning Accurate and Enriched Features for Stereo Image Super-ResolutionCode0
Component Attention Guided Face Super-Resolution Network: CAGFaceCode0
Enhancing Super-Resolution Networks through Realistic Thick-Slice CT SimulationCode0
3DSRnet: Video Super-resolution using 3D Convolutional Neural NetworksCode0
LCSCNet: Linear Compressing Based Skip-Connecting Network for Image Super-ResolutionCode0
COMISR: Compression-Informed Video Super-ResolutionCode0
LD-GAN: Low-Dimensional Generative Adversarial Network for Spectral Image Generation with Variance RegularizationCode0
Learned Block Iterative Shrinkage Thresholding Algorithm for Photothermal Super Resolution ImagingCode0
Enhancing Image Resolution of Solar Magnetograms: A Latent Diffusion Model ApproachCode0
LatticeNet: Towards Lightweight Image Super-resolution with Lattice BlockCode0
Enhancing Image Rescaling using Dual Latent Variables in Invertible Neural NetworkCode0
Learning Multiple Probabilistic Degradation Generators for Unsupervised Real World Image Super ResolutionCode0
Combining Contrastive and Supervised Learning for Video Super-Resolution DetectionCode0
FCSR-GAN: Joint Face Completion and Super-resolution via Multi-task LearningCode0
CoPE: Conditional image generation using Polynomial ExpansionsCode0
Laplacian Pyramid-like AutoencoderCode0
Enhancing Events in Neutrino Telescopes through Deep Learning-Driven Super-ResolutionCode0
Multi-Feature Aggregation in Diffusion Models for Enhanced Face Super-ResolutionCode0
LAP: a Linearize and Project Method for Solving Inverse Problems with Coupled VariablesCode0
LAR-SR: A Local Autoregressive Model for Image Super-ResolutionCode0
Combination of Single and Multi-frame Image Super-resolution: An Analytical PerspectiveCode0
Correction Filter for Single Image Super-Resolution: Robustifying Off-the-Shelf Deep Super-ResolversCode0
Enhancing Amyloid PET Quantification: MRI-Guided Super-Resolution Using Latent Diffusion ModelsCode0
EnhanceNet: Single Image Super-Resolution Through Automated Texture SynthesisCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified