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

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Showing 926–950 of 3874 papers

TitleStatusHype
Deep Video Super-Resolution using HR Optical Flow EstimationCode1
Transformer for Single Image Super-ResolutionCode1
End-to-end Alternating Optimization for Blind Super ResolutionCode1
Deformable 3D Convolution for Video Super-ResolutionCode1
BiMaCoSR: Binary One-Step Diffusion Model Leveraging Flexible Matrix Compression for Real Super-ResolutionCode1
Enhanced Super-Resolution Training via Mimicked Alignment for Real-World ScenesCode1
SGNet: Structure Guided Network via Gradient-Frequency Awareness for Depth Map Super-ResolutionCode1
Ship in Sight: Diffusion Models for Ship-Image Super ResolutionCode1
SHISRCNet: Super-resolution And Classification Network For Low-resolution Breast Cancer Histopathology ImageCode1
Degradation-Aware Self-Attention Based Transformer for Blind Image Super-ResolutionCode1
2-Step Sparse-View CT Reconstruction with a Domain-Specific Perceptual NetworkCode1
Efficient Image Super-Resolution Using Pixel AttentionCode1
Degradation Oriented and Regularized Network for Blind Depth Super-ResolutionCode1
Single Image Super-Resolution Based on Capsule Neural NetworksCode1
Single Image Super-Resolution via a Dual Interactive Implicit Neural NetworkCode1
Single Image Super-Resolution via CNN Architectures and TV-TV MinimizationCode1
Single MR Image Super-Resolution using Generative Adversarial NetworkCode1
SNIPS: Solving Noisy Inverse Problems StochasticallyCode1
Solving Inverse Problems via Diffusion Optimal ControlCode1
An End-to-end Framework For Low-Resolution Remote Sensing Semantic SegmentationCode1
BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder ArchitectureCode1
Efficient Image Super-Resolution using Vast-Receptive-Field AttentionCode1
Uncertainty-Aware Source-Free Adaptive Image Super-Resolution with Wavelet Augmentation TransformerCode1
U2Net: A General Framework with Spatial-Spectral-Integrated Double U-Net for Image FusionCode1
B-Spline Texture Coefficients Estimator for Screen Content Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified