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 351–360 of 3874 papers

TitleStatusHype
Component Divide-and-Conquer for Real-World Image Super-ResolutionCode1
Compression-Aware Video Super-ResolutionCode1
Computing Multiple Image Reconstructions with a Single HypernetworkCode1
Conditional Variational Diffusion ModelsCode1
Conditional Simulation Using Diffusion Schrödinger BridgesCode1
CoDi: Conditional Diffusion Distillation for Higher-Fidelity and Faster Image GenerationCode1
Dual-Camera Super-Resolution with Aligned Attention ModulesCode1
Conditionally Parameterized, Discretization-Aware Neural Networks for Mesh-Based Modeling of Physical SystemsCode1
ARM: Any-Time Super-Resolution MethodCode1
Discovering Distinctive "Semantics" in Super-Resolution NetworksCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified