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 1751–1800 of 3874 papers

TitleStatusHype
Nonparallel High-Quality Audio Super Resolution with Domain Adaptation and Resampling CycleGANsCode1
Conditioning and Sampling in Variational Diffusion Models for Speech Super-ResolutionCode0
Generalized Matrix-Pencil Approach to Estimation of Complex Exponentials with Gapped Data—0
Three more Decades in Array Signal Processing Research: An Optimization and Structure Exploitation Perspective—0
Super-Resolution Based Patch-Free 3D Image Segmentation with High-Frequency GuidanceCode0
A Regularized Conditional GAN for Posterior Sampling in Image Recovery ProblemsCode0
Iris super-resolution using CNNs: is photo-realism important to iris recognition?—0
High-Resolution Image Editing via Multi-Stage Blended DiffusionCode1
Single Image Super-Resolution via a Dual Interactive Implicit Neural NetworkCode1
How Real is Real: Evaluating the Robustness of Real-World Super Resolution—0
Efficient Hair Style Transfer with Generative Adversarial Networks—0
Boomerang: Local sampling on image manifolds using diffusion models—0
Single Image Super-Resolution Using Lightweight Networks Based on Swin Transformer—0
Super-Resolution and Image Re-projection for Iris Recognition—0
Reversed Image Signal Processing and RAW Reconstruction. AIM 2022 Challenge Report—0
Real Image Super-Resolution using GAN through modeling of LR and HR process—0
Provably Convergent Plug & Play Linearized ADMM, applied to Deblurring Spatially Varying KernelsCode0
Video super-resolution for single-photon LIDAR—0
Very Low-Resolution Iris Recognition Via Eigen-Patch Super-Resolution and Matcher Fusion—0
ITSRN++: Stronger and Better Implicit Transformer Network for Continuous Screen Content Image Super-Resolution—0
Scale-Agnostic Super-Resolution in MRI using Feature-Based Coordinate Networks—0
A Codec Information Assisted Framework for Efficient Compressed Video Super-Resolution—0
Deep Learning based Super-Resolution for Medical Volume Visualization with Direct Volume Rendering—0
Blind Super-Resolution for Remote Sensing Images via Conditional Stochastic Normalizing Flows—0
Lightweight Stepless Super-Resolution of Remote Sensing Images via Saliency-Aware Dynamic Routing StrategyCode1
ISTA-Inspired Network for Image Super-Resolution—0
Scene Text Image Super-Resolution via Content Perceptual Loss and Criss-Cross Transformer Blocks—0
CUF: Continuous Upsampling Filters—0
Action Matching: Learning Stochastic Dynamics from SamplesCode1
QMRNet: Quality Metric Regression for EO Image Quality Assessment and Super-ResolutionCode0
Face Super-Resolution with Progressive Embedding of Multi-scale Face Priors—0
A Comparative Study on 1.5T-3T MRI Conversion through Deep Neural Network Models—0
Efficient Image Super-Resolution using Vast-Receptive-Field AttentionCode1
Deep Fourier Up-SamplingCode0
DA-VSR: Domain Adaptable Volumetric Super-Resolution For Medical Images—0
Learning Texture Transformer Network for Light Field Super-Resolution—0
Cost-effective photonic super-resolution millimeter-wave joint radar-communication system using self-coherent detection—0
Super-Resolution by Predicting Offsets: An Ultra-Efficient Super-Resolution Network for Rasterized Images—0
Flexible Alignment Super-Resolution Network for Multi-Contrast MRICode0
A Simple Plugin for Transforming Images to Arbitrary Scales—0
Single Image Super-Resolution Based on Capsule Neural NetworksCode1
Nanoscopic distribution of VAChT and VGLUT3 in striatal cholinergic varicosities suggests colocalization and segregation of the two transporters in synaptic vesicles—0
MuS2: A Real-World Benchmark for Sentinel-2 Multi-Image Super-ResolutionCode0
Rolling Shutter Inversion: Bring Rolling Shutter Images to High Framerate Global Shutter VideoCode1
Imagen Video: High Definition Video Generation with Diffusion Models—0
Accurate Image Restoration with Attention Retractable TransformerCode1
From Face to Natural Image: Learning Real Degradation for Blind Image Super-ResolutionCode1
Make-A-Video: Text-to-Video Generation without Text-Video DataCode1
Deep Sparse and Low-Rank Prior for Hyperspectral Image DenoisingCode0
Multi-scale Attention Network for Single Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified