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 2281–2290 of 3874 papers

TitleStatusHype
Mid-wave infrared super-resolution imaging based on compressive calibration and sampling—0
Millimetre-wave Radar for Low-Cost 3D Imaging: A Performance Study—0
Mimic3D: Thriving 3D-Aware GANs via 3D-to-2D Imitation—0
MIMRS: A Survey on Masked Image Modeling in Remote Sensing—0
Continual Learning-Aided Super-Resolution Scheme for Channel Reconstruction and Generalization in OFDM Systems—0
A Comprehensive Survey of Transformers for Computer Vision—0
Transformers in Vision: A Survey—0
MIRE: Matched Implicit Neural Representations—0
Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging—0
Context Reasoning Attention Network for Image Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified