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 1376–1400 of 3874 papers

TitleStatusHype
Deceptive-NeRF/3DGS: Diffusion-Generated Pseudo-Observations for High-Quality Sparse-View Reconstruction—0
AI-assisted super-resolution cosmological simulations—0
Debiased Subjective Assessment of Real-World Image Enhancement—0
Super-resolution of Time-series Labels for Bootstrapped Event Detection—0
Advancing Supervised Local Learning Beyond Classification with Long-term Feature Bank—0
DDS2M: Self-Supervised Denoising Diffusion Spatio-Spectral Model for Hyperspectral Image Restoration—0
AdaDiffSR: Adaptive Region-aware Dynamic Acceleration Diffusion Model for Real-World Image Super-Resolution—0
Attention-Guided Multi-scale Interaction Network for Face Super-Resolution—0
A Hybrid Registration and Fusion Method for Hyperspectral Super-resolution—0
GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations—0
DC-VSR: Spatially and Temporally Consistent Video Super-Resolution with Video Diffusion Prior—0
DCS-RISR: Dynamic Channel Splitting for Efficient Real-world Image Super-Resolution—0
DCIL: Deep Contextual Internal Learning for Image Restoration and Image Retargeting—0
A hybrid approach of interpolations and CNN to obtain super-resolution—0
CLADE: Cycle Loss Augmented Degradation Enhancement for Unpaired Super-Resolution of Anisotropic Medical Images—0
Global-Local Face Upsampling Network—0
Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolution—0
Harnessing Sparsity over the Continuum: Atomic Norm Minimization for Super Resolution—0
DA-VSR: Domain Adaptable Volumetric Super-Resolution For Medical Images—0
Attention-based Image Upsampling—0
A Hybrid Approach Between Adversarial Generative Networks and Actor-Critic Policy Gradient for Low Rate High-Resolution Image Compression—0
Attention-Aware Face Hallucination via Deep Reinforcement Learning—0
Geometric Distortion Guided Transformer for Omnidirectional Image Super-Resolution—0
Data-Driven Design for Fourier Ptychographic Microscopy—0
A HVS-inspired Attention to Improve Loss Metrics for CNN-based Perception-Oriented Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified