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 791–800 of 3874 papers

TitleStatusHype
Augmented Convolutional LSTMs for Generation of High-Resolution Climate Change ProjectionsCode1
Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance PursuitCode1
Iterative Token Evaluation and Refinement for Real-World Super-ResolutionCode1
Generative Adversarial NetworksCode1
Deep Interleaved Network for Image Super-Resolution With Asymmetric Co-AttentionCode1
DA-MUSIC: Data-Driven DoA Estimation via Deep Augmented MUSIC AlgorithmCode1
Joint Demosaicing and Denoising With Self GuidanceCode1
Panini-Net: GAN Prior Based Degradation-Aware Feature Interpolation for Face RestorationCode1
DeepBedMap: Using a deep neural network to better resolve the bed topography of AntarcticaCode1
Burst Image Restoration and EnhancementCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified