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 176–200 of 3874 papers

TitleStatusHype
Learning Continuous Image Representation with Local Implicit Image FunctionCode2
Learning Trajectory-Aware Transformer for Video Super-ResolutionCode2
Learning Truncated Causal History Model for Video RestorationCode2
AIM 2020 Challenge on Efficient Super-Resolution: Methods and ResultsCode2
Building Bridges across Spatial and Temporal Resolutions: Reference-Based Super-Resolution via Change Priors and Conditional Diffusion ModelCode2
Diffusion Models for Image Restoration and Enhancement -- A Comprehensive SurveyCode2
Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-ResolutionCode2
DiffIR2VR-Zero: Zero-Shot Video Restoration with Diffusion-based Image Restoration ModelsCode2
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse ProblemsCode2
Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differencesCode2
Denoising Diffusion Models for Plug-and-Play Image RestorationCode2
CDFormer:When Degradation Prediction Embraces Diffusion Model for Blind Image Super-ResolutionCode2
On the Generalization of BasicVSR++ to Video Deblurring and DenoisingCode2
Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution with Subpixel FusionCode2
AnimeSR: Learning Real-World Super-Resolution Models for Animation VideosCode2
Deep Constrained Least Squares for Blind Image Super-ResolutionCode2
Denoising Diffusion Restoration ModelsCode2
Contourlet Refinement Gate Framework for Thermal Spectrum Distribution Regularized Infrared Image Super-ResolutionCode2
DifIISR: A Diffusion Model with Gradient Guidance for Infrared Image Super-ResolutionCode2
Efficient and Scalable Point Cloud Generation with Sparse Point-Voxel Diffusion ModelsCode2
Generative Diffusion-based Downscaling for ClimateCode2
CuNeRF: Cube-Based Neural Radiance Field for Zero-Shot Medical Image Arbitrary-Scale Super ResolutionCode1
CutMIB: Boosting Light Field Super-Resolution via Multi-View Image BlendingCode1
CTCNet: A CNN-Transformer Cooperation Network for Face Image Super-ResolutionCode1
CSAKD: Knowledge Distillation with Cross Self-Attention for Hyperspectral and Multispectral Image FusionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified