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 901–925 of 3874 papers

TitleStatusHype
Multi-Scale Implicit Transformer with Re-parameterize for Arbitrary-Scale Super-Resolution—0
Implicit Image-to-Image Schrodinger Bridge for Image RestorationCode0
Decoupled Data Consistency with Diffusion Purification for Image RestorationCode1
Adaptive Multi-modal Fusion of Spatially Variant Kernel Refinement with Diffusion Model for Blind Image Super-Resolution—0
XPSR: Cross-modal Priors for Diffusion-based Image Super-ResolutionCode2
CogView3: Finer and Faster Text-to-Image Generation via Relay DiffusionCode5
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
APISR: Anime Production Inspired Real-World Anime Super-ResolutionCode5
Text-guided Explorable Image Super-resolution—0
ODVista: An Omnidirectional Video Dataset for super-resolution and Quality Enhancement TasksCode1
LoLiSRFlow: Joint Single Image Low-light Enhancement and Super-resolution via Cross-scale Transformer-based Conditional Flow—0
SeD: Semantic-Aware Discriminator for Image Super-ResolutionCode2
Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of ArtifactsCode2
Navigating Beyond Dropout: An Intriguing Solution Towards Generalizable Image Super Resolution—0
CAMixerSR: Only Details Need More "Attention"Code3
Unsupervised Learning of High-resolution Light Field Imaging via Beam Splitter-based Hybrid Lenses—0
Misalignment-Robust Frequency Distribution Loss for Image TransformationCode2
Self-Supervised Learning with Generative Adversarial Networks for Electron Microscopy—0
Simple Base Frame Guided Residual Network for RAW Burst Image Super-ResolutionCode1
Thermodynamics-informed super-resolution of scarce temporal dynamics data—0
SAM-DiffSR: Structure-Modulated Diffusion Model for Image Super-ResolutionCode2
Enhancing Hyperspectral Images via Diffusion Model and Group-Autoencoder Super-resolution NetworkCode1
Generative AI in Vision: A Survey on Models, Metrics and Applications—0
Photon-counting CT using a Conditional Diffusion Model for Super-resolution and Texture-preservation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified