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 731–740 of 3874 papers

TitleStatusHype
DA-MUSIC: Data-Driven DoA Estimation via Deep Augmented MUSIC AlgorithmCode1
Conditionally Parameterized, Discretization-Aware Neural Networks for Mesh-Based Modeling of Physical SystemsCode1
Dual-Camera Super-Resolution with Aligned Attention ModulesCode1
Exploring Separable Attention for Multi-Contrast MR Image Super-ResolutionCode1
Self-Attention for Audio Super-ResolutionCode1
Generalized Real-World Super-Resolution through Adversarial RobustnessCode1
Transformer for Single Image Super-ResolutionCode1
Memory-Augmented Non-Local Attention for Video Super-ResolutionCode1
edge-SR: Super-Resolution For The MassesCode1
Deep Reparametrization of Multi-Frame Super-Resolution and DenoisingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified