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 2251–2275 of 3874 papers

TitleStatusHype
Advancing High-Resolution Video-Language Representation with Large-Scale Video TranscriptionsCode1
Image Super-Resolution Using T-Tetromino Pixels—0
Local Texture Estimator for Implicit Representation FunctionCode1
Fast and Light-Weight Network for Single Frame Structured Illumination Microscopy Super-Resolution—0
A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolution—0
Pansharpening by convolutional neural networks in the full resolution frameworkCode1
Image-specific Convolutional Kernel Modulation for Single Image Super-resolutionCode1
Pixel-Level Kernel Estimation for Blind Super-ResolutionCode0
Small or Far Away? Exploiting Deep Super-Resolution and Altitude Data for Aerial Animal SurveillanceCode0
Explanatory Analysis and Rectification of the Pitfalls in COVID-19 Datasets—0
GDCA: GAN-based single image super resolution with Dual discriminators and Channel Attention—0
Synthetic magnetic resonance images for domain adaptation: Application to fetal brain tissue segmentation—0
S3RP: Self-Supervised Super-Resolution and Prediction for Advection-Diffusion Process—0
Texture-enhanced Light Field Super-resolution with Spatio-Angular Decomposition KernelsCode0
Physics-Informed Neural Operator for Learning Partial Differential EquationsCode1
Frequency-Aware Physics-Inspired Degradation Model for Real-World Image Super-Resolution—0
Remote Sensing Image Super-resolution and Object Detection: Benchmark and State of the Art—0
Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-resolution—0
Multi-Spectral Multi-Image Super-Resolution of Sentinel-2 with Radiometric Consistency Losses and Its Effect on Building Delineation—0
Resampling and super-resolution of hexagonally sampled images using deep learning—0
Blind inverse problems with isolated spikes—0
TranSMS: Transformers for Super-Resolution Calibration in Magnetic Particle ImagingCode1
Deep learning of multi-resolution X-Ray micro-CT images for multi-scale modellingCode1
FREGAN : an application of generative adversarial networks in enhancing the frame rate of videos—0
AdaPool: Exponential Adaptive Pooling for Information-Retaining DownsamplingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified