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 326–350 of 3874 papers

TitleStatusHype
FLowHigh: Towards Efficient and High-Quality Audio Super-Resolution with Single-Step Flow MatchingCode2
Physics-Informed Super-Resolution Diffusion for 6D Phase Space Diagnostics—0
Conditional Mutual Information Based Diffusion Posterior Sampling for Solving Inverse Problems—0
HOGSA: Bimanual Hand-Object Interaction Understanding with 3D Gaussian Splatting Based Data Augmentation—0
STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution—0
Compressed Domain Prior-Guided Video Super-Resolution for Cloud Gaming Content—0
Transformer-Driven Inverse Problem Transform for Fast Blind Hyperspectral Image Dehazing—0
IGAF: Incremental Guided Attention Fusion for Depth Super-Resolution—0
Embedding Similarity Guided License Plate Super Resolution—0
Spk2SRImgNet: Super-Resolve Dynamic Scene from Spike Stream via Motion Aligned Collaborative Filtering—0
Efficient Video Super-Resolution for Real-time Rendering with Decoupled G-buffer Guidance—0
ADD: Attribution-Driven Data Augmentation Framework for Boosting Image Super-Resolution—0
Event-based Video Super-Resolution via State Space Models—0
S2Gaussian: Sparse-View Super-Resolution 3D Gaussian Splatting—0
TSP-Mamba: The Travelling Salesman Problem Meets Mamba for Image Super-resolution and Beyond—0
PatchVSR: Breaking Video Diffusion Resolution Limits with Patch-wise Video Super-Resolution—0
Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual ApproximatorsCode1
MIRE: Matched Implicit Neural Representations—0
Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution—0
SLVR: Super-Light Visual Reconstruction via Blueprint Controllable Convolutions and Exploring Feature Diversity RepresentationCode0
DORNet: A Degradation Oriented and Regularized Network for Blind Depth Super-Resolution—0
BF-STVSR: B-Splines and Fourier---Best Friends for High Fidelity Spatial-Temporal Video Super-ResolutionCode1
Augmenting Perceptual Super-Resolution via Image Quality Predictors—0
VolFormer: Explore More Comprehensive Cube Interaction for Hyperspectral Image Restoration and BeyondCode1
Hazy Low-Quality Satellite Video Restoration Via Learning Optimal Joint Degradation Patterns and Continuous-Scale Super-Resolution Reconstruction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified