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 2101–2125 of 3874 papers

TitleStatusHype
Depth-Independent Depth Completion via Least Square Estimation—0
A Novel Dual Dense Connection Network for Video Super-resolution—0
Adaptive Cross-Layer Attention for Image RestorationCode1
HyperTransformer: A Textural and Spectral Feature Fusion Transformer for PansharpeningCode1
Ad2Attack: Adaptive Adversarial Attack on Real-Time UAV TrackingCode1
Fast Neural Architecture Search for Lightweight Dense Prediction Networks—0
Self-Supervised Learning for Real-World Super-Resolution from Dual Zoomed ObservationsCode1
Towards Bidirectional Arbitrary Image Rescaling: Joint Optimization and Cycle Idempotence—0
Fine-grained Urban Flow Inference with Incomplete DataCode0
Thermographic detection of internal defects using 2D photothermal super resolution reconstruction with sequential laser heating—0
Enhanced Image Reconstruction From Quarter Sampling Measurements Using An Adapted Very Deep Super Resolution Network—0
Spatio-temporal Vision Transformer for Super-resolution MicroscopyCode1
Enhancing Satellite Imagery using Deep Learning for the Sensor To Shooter Timeline—0
One-shot Ultra-high-Resolution Generative Adversarial Network That Synthesizes 16K Images On A Single GPU—0
Conditional Simulation Using Diffusion Schrödinger BridgesCode1
Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution PriorsCode2
Pix2NeRF: Unsupervised Conditional π-GAN for Single Image to Neural Radiance Fields TranslationCode2
Multi-image Super-resolution via Quality Map Associated Attention Network—0
Time Efficient Training of Progressive Generative Adversarial Network using Depthwise Separable Convolution and Super Resolution Generative Adversarial Network—0
Super-resolution GANs of randomly-seeded fieldsCode0
Convolutional Neural Network Modelling for MODIS Land Surface Temperature Super-ResolutionCode1
Disentangling Light Fields for Super-Resolution and Disparity Estimation—0
Mathematical Foundation of Sparsity-based Multi-snapshot Spectral Estimation—0
Rotationally Equivariant Super-Resolution of Velocity Fields in Two-Dimensional Fluids Using Convolutional Neural Networks—0
Computing Multiple Image Reconstructions with a Single HypernetworkCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified