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 551–575 of 3874 papers

TitleStatusHype
Consistent Direct Time-of-Flight Video Depth Super-ResolutionCode1
MedleyVox: An Evaluation Dataset for Multiple Singing Voices SeparationCode1
The Best of Both Worlds: a Framework for Combining Degradation Prediction with High Performance Super-Resolution NetworksCode1
Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: ReportCode1
Self-supervised Character-to-Character Distillation for Text RecognitionCode1
Combining Attention Module and Pixel Shuffle for License Plate Super-ResolutionCode1
Nonparallel High-Quality Audio Super Resolution with Domain Adaptation and Resampling CycleGANsCode1
High-Resolution Image Editing via Multi-Stage Blended DiffusionCode1
Single Image Super-Resolution via a Dual Interactive Implicit Neural NetworkCode1
Lightweight Stepless Super-Resolution of Remote Sensing Images via Saliency-Aware Dynamic Routing StrategyCode1
Action Matching: Learning Stochastic Dynamics from SamplesCode1
Efficient Image Super-Resolution using Vast-Receptive-Field AttentionCode1
Rolling Shutter Inversion: Bring Rolling Shutter Images to High Framerate Global Shutter VideoCode1
Single Image Super-Resolution Based on Capsule Neural NetworksCode1
Accurate Image Restoration with Attention Retractable TransformerCode1
From Face to Natural Image: Learning Real Degradation for Blind Image Super-ResolutionCode1
Make-A-Video: Text-to-Video Generation without Text-Video DataCode1
Multi-scale Attention Network for Single Image Super-ResolutionCode1
A heterogeneous group CNN for image super-resolutionCode1
Real-RawVSR: Real-World Raw Video Super-Resolution with a Benchmark DatasetCode1
Face Super-Resolution Using Stochastic Differential EquationsCode1
HAZE-Net: High-Frequency Attentive Super-Resolved Gaze Estimation in Low-Resolution Face ImagesCode1
KXNet: A Model-Driven Deep Neural Network for Blind Super-ResolutionCode1
Deep Plug-and-Play Prior for Hyperspectral Image RestorationCode1
Model-Guided Multi-Contrast Deep Unfolding Network for MRI Super-resolution ReconstructionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified