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 741–750 of 3874 papers

TitleStatusHype
Face Super-Resolution Using Stochastic Differential EquationsCode1
Face Super-Resolution Through Wasserstein GANsCode1
CABM: Content-Aware Bit Mapping for Single Image Super-Resolution Network with Large InputCode1
C3-STISR: Scene Text Image Super-resolution with Triple CluesCode1
CutMIB: Boosting Light Field Super-Resolution via Multi-View Image BlendingCode1
Adaptive Convolutional Neural Network for Image Super-resolutionCode1
CVAE-GAN: Fine-Grained Image Generation through Asymmetric TrainingCode1
A heterogeneous group CNN for image super-resolutionCode1
Deep Audio Waveform PriorCode1
A New Dataset and Transformer for Stereoscopic Video Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified