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 1801–1825 of 3874 papers

TitleStatusHype
FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurring—0
Super-resolution multi-contrast unbiased eye atlases with deep probabilistic refinement—0
What You See is What You GAN: Rendering Every Pixel for High-Fidelity Geometry in 3D GANs—0
Predicting Future States with Spatial Point Processes in Single Molecule Resolution Spatial Transcriptomics—0
Noise-NeRF: Hide Information in Neural Radiance Fields using Trainable Noise—0
Efficient Hybrid Zoom using Camera Fusion on Mobile Phones—0
Learning Coupled Dictionaries from Unpaired Data for Image Super-Resolution—0
Beyond Subspace Isolation: Many-to-Many Transformer for Light Field Image Super-resolutionCode0
Image Processing GNN: Breaking Rigidity in Super-Resolution—0
Towards Progressive Multi-Frequency Representation for Image WarpingCode0
Super-Resolution Reconstruction from Bayer-Pattern Spike StreamsCode0
Diffusion Models, Image Super-Resolution And Everything: A Survey—0
CoDe: An Explicit Content Decoupling Framework for Image Restoration—0
UGPNet: Universal Generative Prior for Image Restoration—0
Compressing Deep Image Super-resolution Models—0
Image Super-resolution Reconstruction Network based on Enhanced Swin Transformer via Alternating Aggregation of Local-Global Features—0
Single particle algorithms to reveal cellular nanodomain organization—0
Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction—0
Learn From Orientation Prior for Radiograph Super-Resolution: Orientation Operator Transformer—0
A Survey on Super Resolution for video Enhancement Using GAN—0
BSRAW: Improving Blind RAW Image Super-Resolution—0
Super-resolution of THz time-domain images based on low-rank representation—0
A Comprehensive End-to-End Computer Vision Framework for Restoration and Recognition of Low-Quality Engineering DrawingsCode0
Learning Exhaustive Correlation for Spectral Super-Resolution: Where Spatial-Spectral Attention Meets Linear Dependence—0
How Good Are Deep Generative Models for Solving Inverse Problems?—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified