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 526–550 of 3874 papers

TitleStatusHype
Catch-A-Waveform: Learning to Generate Audio from a Single Short ExampleCode1
Deep Video Super-Resolution using HR Optical Flow EstimationCode1
Degradation Oriented and Regularized Network for Blind Depth Super-ResolutionCode1
Deep Reparametrization of Multi-Frame Super-Resolution and DenoisingCode1
Deep Random Projector: Accelerated Deep Image PriorCode1
DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-ResolutionCode1
Antenna Failure Resilience: Deep Learning-Enabled Robust DOA Estimation with Single Snapshot Sparse ArraysCode1
Deep Plug-and-Play Super-Resolution for Arbitrary Blur KernelsCode1
Deep Posterior Distribution-based Embedding for Hyperspectral Image Super-resolutionCode1
Deep Semantic Statistics Matching (D2SM) Denoising NetworkCode1
Deep Model-Based Super-Resolution with Non-uniform BlurCode1
3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised LearningCode1
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super ResolutionCode1
Advancing High-Resolution Video-Language Representation with Large-Scale Video TranscriptionsCode1
Deep Plug-and-Play Prior for Hyperspectral Image RestorationCode1
Deep Space-Time Video Upsampling NetworksCode1
Distillation-Driven Diffusion Model for Multi-Scale MRI Super-Resolution: Make 1.5T MRI Great AgainCode1
Deep Learning-Based Multiband Signal Fusion for 3-D SAR Super-ResolutionCode1
Deep Learning-based Face Super-Resolution: A SurveyCode1
Deep learning architectural designs for super-resolution of noisy imagesCode1
Deep Interleaved Network for Image Super-Resolution With Asymmetric Co-AttentionCode1
Deep Learning-Based CKM Construction with Image Super-ResolutionCode1
Deep Learning-Driven Ultra-High-Definition Image Restoration: A SurveyCode1
Deep Face Super-Resolution with Iterative Collaboration between Attentive Recovery and Landmark EstimationCode1
Cascaded Temporal Updating Network for Efficient Video Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified