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 1701–1750 of 3874 papers

TitleStatusHype
Space-Time Video Super-resolution with Neural Operator—0
Dynamic Deep Learning Based Super-Resolution For The Shallow Water Equations—0
Gull: A Generative Multifunctional Audio Codec—0
CycleINR: Cycle Implicit Neural Representation for Arbitrary-Scale Volumetric Super-Resolution of Medical Data—0
Efficient Learnable Collaborative Attention for Single Image Super-Resolution—0
PointSAGE: Mesh-independent superresolution approach to fluid flow predictions—0
Power-Efficient Image Storage: Leveraging Super Resolution Generative Adversarial Network for Sustainable Compression and Reduced Carbon Footprint—0
Real-GDSR: Real-World Guided DSM Super-Resolution via Edge-Enhancing Residual Network—0
CSR-dMRI: Continuous Super-Resolution of Diffusion MRI with Anatomical Structure-assisted Implicit Neural Representation Learning—0
Translation-based Video-to-Video Synthesis—0
Knowledge Distillation with Multi-granularity Mixture of Priors for Image Super-Resolution—0
Distortion-aware super-resolution for planetary exploration imagesCode0
RefQSR: Reference-based Quantization for Image Super-Resolution Networks—0
Super-Resolution Analysis for Landfill Waste Classification—0
Video Interpolation with Diffusion Models—0
SGDFormer: One-stage Transformer-based Architecture for Cross-Spectral Stereo Image Guided Denoising—0
Super-Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using SDO/HMI Data and an Attention-Aided Convolutional Neural Network—0
Lift3D: Zero-Shot Lifting of Any 2D Vision Model to 3D—0
SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational AutoencoderCode0
Masked Autoencoders are PDE LearnersCode0
Climate Downscaling: A Deep-Learning Based Super-resolution Model of Precipitation Data with Attention Block and Skip Connections—0
Self-Adaptive Reality-Guided Diffusion for Artifact-Free Super-ResolutionCode0
A Study in Dataset Pruning for Image Super-Resolution—0
Learning Spatial Adaptation and Temporal Coherence in Diffusion Models for Video Super-Resolution—0
Self-STORM: Deep Unrolled Self-Supervised Learning for Super-Resolution MicroscopyCode0
LaMAR: Laplacian Pyramid for Multimodal Adaptive Super Resolution (Student Abstract)—0
Time-series Initialization and Conditioning for Video-agnostic Stabilization of Video Super-Resolution using Recurrent Networks—0
Deep Generative Model based Rate-Distortion for Image Downscaling AssessmentCode0
Hyperspectral Neural Radiance Fields—0
QSMDiff: Unsupervised 3D Diffusion Models for Quantitative Susceptibility Mapping—0
Using Super-Resolution Imaging for Recognition of Low-Resolution Blurred License Plates: A Comparative Study of Real-ESRGAN, A-ESRGAN, and StarSRGAN—0
A Wideband Distributed Massive MIMO Channel Sounder for Communication and Sensing—0
PAON: A New Neuron Model using Padé Approximants—0
CasSR: Activating Image Power for Real-World Image Super-Resolution—0
Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient Viewpoint—0
SemanticHuman-HD: High-Resolution Semantic Disentangled 3D Human Generation—0
A General Method to Incorporate Spatial Information into Loss Functions for GAN-based Super-resolution Models—0
Arbitrary-Scale Image Generation and Upsampling using Latent Diffusion Model and Implicit Neural Decoder—0
Deep unfolding Network for Hyperspectral Image Super-Resolution with Automatic Exposure Correction—0
PFStorer: Personalized Face Restoration and Super-Resolution—0
Learning Hierarchical Color Guidance for Depth Map Super-Resolution—0
Learning Correction Errors via Frequency-Self Attention for Blind Image Super-Resolution—0
Multi-Scale Implicit Transformer with Re-parameterize for Arbitrary-Scale Super-Resolution—0
Implicit Image-to-Image Schrodinger Bridge for Image RestorationCode0
Adaptive Multi-modal Fusion of Spatially Variant Kernel Refinement with Diffusion Model for Blind Image Super-Resolution—0
Low-Res Leads the Way: Improving Generalization for Super-Resolution by Self-Supervised Learning—0
UB-FineNet: Urban Building Fine-grained Classification Network for Open-access Satellite Images—0
Text-guided Explorable Image Super-resolution—0
Navigating Beyond Dropout: An Intriguing Solution Towards Generalizable Image Super Resolution—0
LoLiSRFlow: Joint Single Image Low-light Enhancement and Super-resolution via Cross-scale Transformer-based Conditional Flow—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified