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 561–570 of 3874 papers

TitleStatusHype
Frequency Estimation Using Complex-Valued Shifted Window TransformerCode1
Creating High Resolution Images with a Latent Adversarial GeneratorCode1
A Systematic Survey of Deep Learning-based Single-Image Super-ResolutionCode1
Cascaded Temporal Updating Network for Efficient Video Super-ResolutionCode1
Cross-Scope Spatial-Spectral Information Aggregation for Hyperspectral Image Super-ResolutionCode1
Cascaded Local Implicit Transformer for Arbitrary-Scale Super-ResolutionCode1
3D Human Pose, Shape and Texture from Low-Resolution Images and VideosCode1
Frequency Domain-based Perceptual Loss for Super ResolutionCode1
Cross-receptive Focused Inference Network for Lightweight Image Super-ResolutionCode1
From Coarse to Fine: Hierarchical Pixel Integration for Lightweight Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified