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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 891–900 of 3874 papers

TitleStatusHype
Align your Latents: High-Resolution Video Synthesis with Latent Diffusion ModelsCode1
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super ResolutionCode1
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image DenoisingCode1
Deep Plug-and-Play Prior for Hyperspectral Image RestorationCode1
EDVR: Video Restoration with Enhanced Deformable Convolutional NetworksCode1
Deep Posterior Distribution-based Embedding for Hyperspectral Image Super-resolutionCode1
Edge-enhanced Feature Distillation Network for Efficient Super-ResolutionCode1
edge-SR: Super-Resolution For The MassesCode1
ECAMP: Entity-centered Context-aware Medical Vision Language Pre-trainingCode1
BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable AlignmentCode1
Show:102550
← PrevPage 90 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified