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 2371–2380 of 3874 papers

TitleStatusHype
Compressive Holographic Video—0
Compressing GANs using Knowledge Distillation—0
Multi-image Super-resolution via Quality Map Associated Attention Network—0
Suppressing Model Overfitting for Image Super-Resolution Networks—0
Multi-Label Scene Classification in Remote Sensing Benefits from Image Super-Resolution—0
Multi-level Encoder-Decoder Architectures for Image Restoration—0
Multi-Level Feature Fusion Mechanism for Single Image Super-Resolution—0
Trustworthy modelling of atmospheric formaldehyde powered by deep learning—0
Trustworthy SR: Resolving Ambiguity in Image Super-resolution via Diffusion Models and Human Feedback—0
A comparative study of various Deep Learning techniques for spatio-temporal Super-Resolution reconstruction of Forced Isotropic Turbulent flows—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified