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 151–200 of 3874 papers

TitleStatusHype
Generalized and Efficient 2D Gaussian Splatting for Arbitrary-scale Super-ResolutionCode2
Dual Aggregation Transformer for Image Super-ResolutionCode2
DVMSR: Distillated Vision Mamba for Efficient Super-ResolutionCode2
CDFormer:When Degradation Prediction Embraces Diffusion Model for Blind Image Super-ResolutionCode2
A Dynamic Kernel Prior Model for Unsupervised Blind Image Super-ResolutionCode2
CMGAN: Conformer-Based Metric-GAN for Monaural Speech EnhancementCode2
AnySR: Realizing Image Super-Resolution as Any-Scale, Any-ResourceCode2
AERO: Audio Super Resolution in the Spectral DomainCode2
DOVE: Efficient One-Step Diffusion Model for Real-World Video Super-ResolutionCode2
EAMamba: Efficient All-Around Vision State Space Model for Image RestorationCode2
DifIISR: A Diffusion Model with Gradient Guidance for Infrared Image Super-ResolutionCode2
Arbitrary-Scale Video Super-Resolution with Structural and Textural PriorsCode2
Distillation-Free One-Step Diffusion for Real-World Image Super-ResolutionCode2
CDFormer: When Degradation Prediction Embraces Diffusion Model for Blind Image Super-ResolutionCode2
CogView: Mastering Text-to-Image Generation via TransformersCode2
All-In-One Medical Image Restoration via Task-Adaptive RoutingCode2
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse ProblemsCode2
Image Restoration with Mean-Reverting Stochastic Differential EquationsCode2
Immersive Neural Graphics PrimitivesCode2
Implicit Diffusion Models for Continuous Super-ResolutionCode2
Distillation-Supervised Convolutional Low-Rank Adaptation for Efficient Image Super-ResolutionCode2
A Survey of Deep Face Restoration: Denoise, Super-Resolution, Deblur, Artifact RemovalCode2
IRSRMamba: Infrared Image Super-Resolution via Mamba-based Wavelet Transform Feature Modulation ModelCode2
Kandinsky 3.0 Technical ReportCode2
Effective Diffusion Transformer Architecture for Image Super-ResolutionCode2
Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-ResolutionCode2
Denoising Diffusion Restoration ModelsCode2
Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differencesCode2
Denoising Diffusion Models for Plug-and-Play Image RestorationCode2
DiffIR2VR-Zero: Zero-Shot Video Restoration with Diffusion-based Image Restoration ModelsCode2
Neural Fields with Thermal Activations for Arbitrary-Scale Super-ResolutionCode2
NTIRE 2025 Challenge on Image Super-Resolution (4): Methods and ResultsCode2
AIM 2020 Challenge on Efficient Super-Resolution: Methods and ResultsCode2
AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and ResultsCode2
Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution with Subpixel FusionCode2
CFAT: Unleashing Triangular Windows for Image Super-resolutionCode2
AutoLUT: LUT-Based Image Super-Resolution with Automatic Sampling and Adaptive Residual LearningCode2
Partial Large Kernel CNNs for Efficient Super-ResolutionCode2
Perceive, Understand and Restore: Real-World Image Super-Resolution with Autoregressive Multimodal Generative ModelsCode2
Auto-Encoded Supervision for Perceptual Image Super-ResolutionCode2
Building Bridges across Spatial and Temporal Resolutions: Reference-Based Super-Resolution via Change Priors and Conditional Diffusion ModelCode2
CogView2: Faster and Better Text-to-Image Generation via Hierarchical TransformersCode2
Deep Constrained Least Squares for Blind Image Super-ResolutionCode2
Diffusion Models for Image Restoration and Enhancement -- A Comprehensive SurveyCode2
Efficient and Scalable Point Cloud Generation with Sparse Point-Voxel Diffusion ModelsCode2
Generative Diffusion-based Downscaling for ClimateCode2
Brain Graph Super-Resolution Using Adversarial Graph Neural Network with Application to Functional Brain ConnectivityCode1
Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain ImagingCode1
Boosting Video Super Resolution with Patch-Based Temporal Redundancy OptimizationCode1
BrainBERT: Self-supervised representation learning for intracranial recordingsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified