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 3311–3320 of 3874 papers

TitleStatusHype
New Techniques for Preserving Global Structure and Denoising with Low Information Loss in Single-Image Super-ResolutionCode0
COMISR: Compression-Informed Video Super-ResolutionCode0
Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object RepresentationCode0
Combining Contrastive and Supervised Learning for Video Super-Resolution DetectionCode0
Multitemporal and multispectral data fusion for super-resolution of Sentinel-2 imagesCode0
Exemplar Guided Face Image Super-Resolution without Facial LandmarksCode0
Multi-scale super-resolution generation of low-resolution scanned pathological imagesCode0
Multi-scale Residual Network for Image Super-ResolutionCode0
Evaluating Robustness of Deep Image Super-Resolution against Adversarial AttacksCode0
Ensemble Super-Resolution with A Reference DatasetCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified