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 161–170 of 3874 papers

TitleStatusHype
Immersive Neural Graphics PrimitivesCode2
AERO: Audio Super Resolution in the Spectral DomainCode2
Blur Interpolation Transformer for Real-World Motion from BlurCode2
A Survey of Deep Face Restoration: Denoise, Super-Resolution, Deblur, Artifact RemovalCode2
SuperYOLO: Super Resolution Assisted Object Detection in Multimodal Remote Sensing ImageryCode2
Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and RestorationCode2
CMGAN: Conformer-Based Metric-GAN for Monaural Speech EnhancementCode2
Text2Light: Zero-Shot Text-Driven HDR Panorama GenerationCode2
AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and ResultsCode2
Towards Lightweight Super-Resolution with Dual Regression LearningCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified