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 626–650 of 3874 papers

TitleStatusHype
Equivalent Transformation and Dual Stream Network Construction for Mobile Image Super-ResolutionCode1
Angular Super-Resolution in Diffusion MRI with a 3D Recurrent Convolutional AutoencoderCode1
Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-ResolutionCode1
ESSAformer: Efficient Transformer for Hyperspectral Image Super-resolutionCode1
Component Divide-and-Conquer for Real-World Image Super-ResolutionCode1
EventSR: From Asynchronous Events to Image Reconstruction, Restoration, and Super-Resolution via End-to-End Adversarial LearningCode1
Designing a Practical Degradation Model for Deep Blind Image Super-ResolutionCode1
Deformable 3D Convolution for Video Super-ResolutionCode1
Exploiting Raw Images for Real-Scene Super-ResolutionCode1
DeFMO: Deblurring and Shape Recovery of Fast Moving ObjectsCode1
Exploring Semantic Feature Discrimination for Perceptual Image Super-Resolution and Opinion-Unaware No-Reference Image Quality AssessmentCode1
Exploring the Low-Pass Filtering Behavior in Image Super-ResolutionCode1
Extremely Lightweight Quantization Robust Real-Time Single-Image Super Resolution for Mobile DevicesCode1
Degradation-Aware Self-Attention Based Transformer for Blind Image Super-ResolutionCode1
Deep Video Super-Resolution using HR Optical Flow EstimationCode1
Deep Unfolding Network for Image Super-ResolutionCode1
DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional FlowsCode1
AeroRIT: A New Scene for Hyperspectral Image AnalysisCode1
DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution ModelsCode1
Fast Monte Carlo Rendering via Multi-Resolution SamplingCode1
Computing Multiple Image Reconstructions with a Single HypernetworkCode1
DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-ResolutionCode1
CoDi: Conditional Diffusion Distillation for Higher-Fidelity and Faster Image GenerationCode1
Feature Distillation Interaction Weighting Network for Lightweight Image Super-ResolutionCode1
Deep Reparametrization of Multi-Frame Super-Resolution and DenoisingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified