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 1401–1425 of 3874 papers

TitleStatusHype
G-PCC Post-Processing Using Fractional 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
Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation Models—0
DAEs for Linear Inverse Problems: Improved Recovery with Provable Guarantees—0
A High-Performance Accelerator for Super-Resolution Processing on Embedded GPU—0
A High-Frequency Focused Network for Lightweight Single Image Super-Resolution—0
A 3D super-resolution of wind fields via physics-informed pixel-wise self-attention generative adversarial network—0
D2C-SR: A Divergence to Convergence Approach for Image Super-Resolution—0
A Three-Player GAN for Super-Resolution in Magnetic Resonance Imaging—0
CycMuNet+: Cycle-Projected Mutual Learning for Spatial-Temporal Video Super-Resolution—0
ATGV-Net: Accurate Depth Super-Resolution—0
Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Model—0
GRAM-HD: 3D-Consistent Image Generation at High Resolution with Generative Radiance Manifolds—0
CycleINR: Cycle Implicit Neural Representation for Arbitrary-Scale Volumetric Super-Resolution of Medical Data—0
Cycle Consistency-based Uncertainty Quantification of Neural Networks in Inverse Imaging Problems—0
CWT-Net: Super-resolution of Histopathology Images Using a Cross-scale Wavelet-based Transformer—0
A Survey of Deep Learning Video Super-Resolution—0
Cutting-Edge Techniques for Depth Map Super-Resolution—0
ATASI-Net: An Efficient Sparse Reconstruction Network for Tomographic SAR Imaging with Adaptive Threshold—0
Global Spatial-Temporal Information-based Residual ConvLSTM for Video Space-Time Super-Resolution—0
Global Stress Generation and Spatiotemporal Super-Resolution Physics-Informed Operator under Dynamic Loading for Two-Phase Random Materials—0
CUF: Continuous Upsampling Filters—0
Cuboid-Net: A Multi-Branch Convolutional Neural Network for Joint Space-Time Video Super Resolution—0
A GPU-Accelerated Light-field Super-resolution Framework Based on Mixed Noise Model and Weighted Regularization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified