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 1001–1025 of 3874 papers

TitleStatusHype
Mitigating Artifacts in Real-World Video Super-Resolution ModelsCode1
Diffusion-based Blind Text Image Super-ResolutionCode1
An Arbitrary Scale Super-Resolution Approach for 3D MR Images via Implicit Neural RepresentationCode1
ML-SIM: A deep neural network for reconstruction of structured illumination microscopy imagesCode1
Local Motion and Contrast Priors Driven Deep Network for Infrared Small Target Super-ResolutionCode1
An efficient CNN for spectral reconstruction from RGB imagesCode1
Multimodal Image Synthesis with Conditional Implicit Maximum Likelihood EstimationCode1
Diffusion Models Beat GANs on Image ClassificationCode1
Real-time 6K Image Rescaling with Rate-distortion OptimizationCode1
DiSR-NeRF: Diffusion-Guided View-Consistent Super-Resolution NeRFCode1
MoEDiff-SR: Mixture of Experts-Guided Diffusion Model for Region-Adaptive MRI Super-ResolutionCode1
Multi-Image Super-Resolution for Remote Sensing using Deep Recurrent NetworksCode1
Diffusion Prior Interpolation for Flexibility Real-World Face Super-ResolutionCode1
MoTIF: Learning Motion Trajectories with Local Implicit Neural Functions for Continuous Space-Time Video Super-ResolutionCode1
Multimodal Multi-Head Convolutional Attention with Various Kernel Sizes for Medical Image Super-ResolutionCode1
DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-ResolutionCode1
Single-subject Multi-contrast MRI Super-resolution via Implicit Neural RepresentationsCode1
MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shiftingCode1
Boosting Single Image Super-Resolution via Partial Channel ShiftingCode1
MuCAN: Multi-Correspondence Aggregation Network for Video Super-ResolutionCode1
Boosting Video Super Resolution with Patch-Based Temporal Redundancy OptimizationCode1
DisC-Diff: Disentangled Conditional Diffusion Model for Multi-Contrast MRI Super-ResolutionCode1
Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain ImagingCode1
Brain Graph Super-Resolution Using Adversarial Graph Neural Network with Application to Functional Brain ConnectivityCode1
Distillation-Driven Diffusion Model for Multi-Scale MRI Super-Resolution: Make 1.5T MRI Great AgainCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified