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 2961–2970 of 3874 papers

TitleStatusHype
AFN: Attentional Feedback Network based 3D Terrain Super-ResolutionCode0
Spatial Frequency Bias in Convolutional Generative Adversarial Networks—0
High Quality Remote Sensing Image Super-Resolution Using Deep Memory Connected Network—0
Deformable Kernel Convolutional Network for Video Extreme Super-Resolution—0
FAN: Frequency Aggregation Network for Real Image Super-resolution—0
AIM 2020 Challenge on Video Temporal Super-Resolution—0
Deep Selective Combinatorial Embedding and Consistency Regularization for Light Field Super-resolution—0
ADMM-Net for Communication Interference Removal in Stepped-Frequency Radar—0
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results—0
Deep Artifact-Free Residual Network for Single Image Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified