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 1051–1100 of 3874 papers

TitleStatusHype
Iterative Token Evaluation and Refinement for Real-World Super-ResolutionCode1
AniRes2D: Anisotropic Residual-enhanced Diffusion for 2D MR Super-Resolution—0
Training Neural Networks on RAW and HDR Images for Restoration TasksCode1
Kandinsky 3.0 Technical ReportCode2
J-Net: Improved U-Net for Terahertz Image Super-Resolution—0
TMSR: Tiny Multi-path CNNs for Super Resolution—0
Conditional Variational Diffusion ModelsCode1
SRTransGAN: Image Super-Resolution using Transformer based Generative Adversarial Network—0
Generative Powers of Ten—0
ESTformer: Transformer Utilizing Spatiotemporal Dependencies for Electroencaphalogram Super-resolution—0
Joint Multiple FMCW Chirp Sequence Processing for Velocity Estimation and Ambiguity Resolving—0
Spectral-wise Implicit Neural Representation for Hyperspectral Image Reconstruction—0
Feature Aggregating Network with Inter-Frame Interaction for Efficient Video Super-Resolution—0
Spatial-Temporal Contrasting for Fine-Grained Urban Flow InferenceCode1
Motion-Guided Latent Diffusion for Temporally Consistent Real-world Video Super-resolutionCode1
Infrared Image Super-Resolution via GAN—0
DFU: scale-robust diffusion model for zero-shot super-resolution image generationCode0
DREAM: Diffusion Rectification and Estimation-Adaptive ModelsCode1
DifAugGAN: A Practical Diffusion-style Data Augmentation for GAN-based Single Image Super-resolution—0
HiPA: Enabling One-Step Text-to-Image Diffusion Models via High-Frequency-Promoting Adaptation—0
PEAN: A Diffusion-Based Prior-Enhanced Attention Network for Scene Text Image Super-ResolutionCode1
Zooming Out on Zooming In: Advancing Super-Resolution for Remote SensingCode2
Neural Fields with Thermal Activations for Arbitrary-Scale Super-ResolutionCode2
Cross-Scope Spatial-Spectral Information Aggregation for Hyperspectral Image Super-ResolutionCode1
Super-Resolution through StyleGAN Regularized Latent Search: A Realism-Fidelity Trade-off—0
Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain ImagingCode1
SeeSR: Towards Semantics-Aware Real-World Image Super-ResolutionCode4
CoSeR: Bridging Image and Language for Cognitive Super-ResolutionCode2
High-resolution Multi-spectral Image Guided DEM Super-resolution using Sinkhorn Regularized Adversarial Network—0
LFSRDiff: Light Field Image Super-Resolution via Diffusion ModelsCode1
Enhancing Perceptual Quality in Video Super-Resolution through Temporally-Consistent Detail Synthesis using Diffusion ModelsCode1
FLAIR: A Conditional Diffusion Framework with Applications to Face Video RestorationCode0
Ultra-Range Gesture Recognition using a Web-Camera in Human-Robot Interaction—0
Resolution- and Stimulus-agnostic Super-Resolution of Ultra-High-Field Functional MRI: Application to Visual Studies—0
Image Super-Resolution with Text Prompt DiffusionCode1
Deep Learning for Automatic Strain Quantification in Arrhythmogenic Right Ventricular Cardiomyopathy—0
SinSR: Diffusion-Based Image Super-Resolution in a Single StepCode0
Recognition-Guided Diffusion Model for Scene Text Image Super-Resolution—0
HierSpeech++: Bridging the Gap between Semantic and Acoustic Representation of Speech by Hierarchical Variational Inference for Zero-shot Speech SynthesisCode3
Swift Parameter-free Attention Network for Efficient Super-ResolutionCode2
Efficient Model Agnostic Approach for Implicit Neural Representation Based Arbitrary-Scale Image Super-Resolution—0
Generalized super-resolution 4D Flow MRI x2013 using ensemble learning to extend across the cardiovascular systemCode0
LATIS: Lambda Abstraction-based Thermal Image Super-resolution—0
Combined Channel and Spatial Attention-based Stereo Endoscopic Image Super-Resolution—0
DIFFNAT: Improving Diffusion Image Quality Using Natural Image Statistics—0
Redefining Super-Resolution: Fine-mesh PDE predictions without classical simulations—0
Scene Text Image Super-resolution based on Text-conditional Diffusion ModelsCode1
Emu Edit: Precise Image Editing via Recognition and Generation Tasks—0
DSR-Diff: Depth Map Super-Resolution with Diffusion ModelCode0
Learning to Reconstruct Accelerated MRI Through K-space Cold Diffusion without NoiseCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified