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 1101–1110 of 3874 papers

TitleStatusHype
Multi-Feature Aggregation in Diffusion Models for Enhanced Face Super-ResolutionCode0
An Adversarial Generative Network Designed for High-Resolution Monocular Depth Estimation from 2D HiRISE Images of MarsCode0
Multiframe Motion Coupling for Video Super ResolutionCode0
Dense xUnit NetworksCode0
MSFNet-CPD: Multi-Scale Cross-Modal Fusion Network for Crop Pest DetectionCode0
Multigrid Backprojection Super-Resolution and Deep Filter VisualizationCode0
Regularization by Neural Style Transfer for MRI Field-Transfer Reconstruction with Limited DataCode0
Denoising Prior Driven Deep Neural Network for Image RestorationCode0
Denoising Graph Super-Resolution towards Improved Collider Event ReconstructionCode0
Accelerating the Training of Video Super-Resolution ModelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified