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 2301–2350 of 3874 papers

TitleStatusHype
Super-Resolution Based Patch-Free 3D Image Segmentation with High-Frequency GuidanceCode0
Iris super-resolution using CNNs: is photo-realism important to iris recognition?—0
A Regularized Conditional GAN for Posterior Sampling in Image Recovery ProblemsCode0
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
ISTA-Inspired Network for Image Super-Resolution—0
Blind Super-Resolution for Remote Sensing Images via Conditional Stochastic Normalizing Flows—0
Scene Text Image Super-Resolution via Content Perceptual Loss and Criss-Cross Transformer Blocks—0
CUF: Continuous Upsampling Filters—0
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
DA-VSR: Domain Adaptable Volumetric Super-Resolution For Medical Images—0
Deep Fourier Up-SamplingCode0
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
Learning Texture Transformer Network for Light Field Super-Resolution—0
Flexible Alignment Super-Resolution Network for Multi-Contrast MRICode0
A Simple Plugin for Transforming Images to Arbitrary Scales—0
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
Imagen Video: High Definition Video Generation with Diffusion Models—0
Low-Resolution Action Recognition for Tiny Actions Challenge—0
Deep Sparse and Low-Rank Prior for Hyperspectral Image DenoisingCode0
Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advances—0
Scaling Laws For Deep Learning Based Image ReconstructionCode0
DELTAR: Depth Estimation from a Light-weight ToF Sensor and RGB Image—0
Effective Invertible Arbitrary Image Rescaling—0
Deep generative model super-resolves spatially correlated multiregional climate data—0
Analytic Optimization-Based Microbubble Tracking in Ultrasound Super-Resolution Microscopy—0
3D Super-Resolution Imaging Method for Distributed Millimeter-wave Automotive Radar System—0
Gemino: Practical and Robust Neural Compression for Video Conferencing—0
Multi-Field De-interlacing using Deformable Convolution Residual Blocks and Self-Attention—0
Recurrent Super-Resolution Method for Enhancing Low Quality Thermal Facial Data—0
Diabetic foot ulcers monitoring by employing super resolution and noise reduction deep learning techniques—0
Synthesis of realistic fetal MRI with conditional Generative Adversarial Networks—0
Perception-Distortion Trade-off in the SR Space Spanned by Flow Models—0
MMSR: Multiple-Model Learned Image Super-Resolution Benefiting From Class-Specific Image Priors—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified