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 2291–2300 of 3874 papers

TitleStatusHype
Fusion of complementary 2D and 3D mesostructural datasets using generative adversarial networksCode1
Toward Real-world Image Super-resolution via Hardware-based Adaptive Degradation Models—0
ERQA: Edge-Restoration Quality Assessment for Video Super-ResolutionCode1
In-Orbit Lunar Satellite Image Super Resolution for Selective Data Transmission—0
Boosting Lightweight Single Image Super-resolution via Joint-distillationCode0
Scene Text Image Super-Resolution via Parallelly Contextual Attention NetworkCode0
Locally Adaptive Structure and Texture Similarity for Image Quality Assessment—0
EFENet: Reference-based Video Super-Resolution with Enhanced Flow EstimationCode1
Optical Flow Reusing for High-Efficiency Space-Time Video Super Resolution—0
Deep Fusion Prior for Plenoptic Super-Resolution All-in-Focus ImagingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified