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 601–625 of 3874 papers

TitleStatusHype
GSR4B: Biomass Map Super-Resolution with Sentinel-1/2 GuidanceCode1
A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary GeometriesCode1
Heterogeneous Mixture of Experts for Remote Sensing Image Super-ResolutionCode1
Deep Interleaved Network for Image Super-Resolution With Asymmetric Co-AttentionCode1
CNN-generated images are surprisingly easy to spot... for nowCode1
Human Pose Estimation on Privacy-Preserving Low-Resolution Depth ImagesCode1
CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed TomographyCode1
3D Registration of pre-surgical prostate MRI and histopathology images via super-resolution volume reconstructionCode1
CTCNet: A CNN-Transformer Cooperation Network for Face Image Super-ResolutionCode1
Deep Learning-Based Multiband Signal Fusion for 3-D SAR Super-ResolutionCode1
CuNeRF: Cube-Based Neural Radiance Field for Zero-Shot Medical Image Arbitrary-Scale Super ResolutionCode1
Cross-View Hierarchy Network for Stereo Image Super-ResolutionCode1
Angular Super-Resolution in Diffusion MRI with a 3D Recurrent Convolutional AutoencoderCode1
Deep Learning-Driven Ultra-High-Definition Image Restoration: A SurveyCode1
CSAKD: Knowledge Distillation with Cross Self-Attention for Hyperspectral and Multispectral Image FusionCode1
Collapsible Linear Blocks for Super-Efficient Super ResolutionCode1
A Practical Contrastive Learning Framework for Single-Image Super-ResolutionCode1
Real-time 6K Image Rescaling with Rate-distortion OptimizationCode1
Deep learning techniques for blind image super-resolution: A high-scale multi-domain perspective evaluationCode1
Deep learning of multi-resolution X-Ray micro-CT images for multi-scale modellingCode1
Combining Attention Module and Pixel Shuffle for License Plate Super-ResolutionCode1
Global Learnable Attention for Single Image Super-ResolutionCode1
Cross-Scale Internal Graph Neural Network for Image Super-ResolutionCode1
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super ResolutionCode1
Cross-Scope Spatial-Spectral Information Aggregation for Hyperspectral Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified