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 1326–1350 of 3874 papers

TitleStatusHype
Real-World Video for Zoom Enhancement based on Spatio-Temporal Coupling—0
Creating Realistic Anterior Segment Optical Coherence Tomography Images using Generative Adversarial Networks—0
Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image AttenuationCode1
Directional diffusion models for graph representation learning—0
Minimalist and High-Quality Panoramic Imaging with PSF-aware TransformersCode1
Super-Resolution of BVOC Emission Maps Via Domain AdaptationCode0
DiffuseIR:Diffusion Models For Isotropic Reconstruction of 3D Microscopic Images—0
Dynamic Implicit Image Function for Efficient Arbitrary-Scale Image RepresentationCode1
HSR-Diff:Hyperspectral Image Super-Resolution via Conditional Diffusion Models—0
Using super-resolution for enhancing visual perception and segmentation performance in veterinary cytology—0
Optical Coherence Tomography Image Enhancement via Block Hankelization and Low Rank Tensor Network Approximation—0
Evaluating Loss Functions and Learning Data Pre-Processing for Climate Downscaling Deep Learning Models—0
Super-resolving sparse observations in partial differential equations: A physics-constrained convolutional neural network approach—0
Super-Resolution Radar Imaging with Sparse Arrays Using a Deep Neural Network Trained with Enhanced Virtual DataCode1
FALL-E: A Foley Sound Synthesis Model and StrategiesCode1
CANDID: Correspondence AligNment for Deep-burst Image Denoising—0
Deep learning techniques for blind image super-resolution: A high-scale multi-domain perspective evaluationCode1
Generalizable One-shot Neural Head Avatar—0
Effects of Data Enrichment with Image Transformations on the Performance of Deep Networks—0
TransMRSR: Transformer-based Self-Distilled Generative Prior for Brain MRI Super-ResolutionCode1
Learning Image-Adaptive Codebooks for Class-Agnostic Image Restoration—0
SARN: Structurally-Aware Recurrent Network for Spatio-Temporal DisaggregationCode0
2DeteCT -- A large 2D expandable, trainable, experimental Computed Tomography dataset for machine learningCode1
HRTF upsampling with a generative adversarial network using a gnomonic equiangular projectionCode1
HQ-50K: A Large-scale, High-quality Dataset for Image RestorationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified