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 771–780 of 3874 papers

TitleStatusHype
Bilateral Event Mining and Complementary for Event Stream Super-ResolutionCode1
IRSRMamba: Infrared Image Super-Resolution via Mamba-based Wavelet Transform Feature Modulation ModelCode2
Frequency-Domain Refinement with Multiscale Diffusion for Super Resolution—0
Large coordinate kernel attention network for lightweight image super-resolution—0
Perception- and Fidelity-aware Reduced-Reference Super-Resolution Image Quality Assessment—0
NAFRSSR: a Lightweight Recursive Network for Efficient Stereo Image Super-ResolutionCode0
CDFormer:When Degradation Prediction Embraces Diffusion Model for Blind Image Super-ResolutionCode2
Exploring the Low-Pass Filtering Behavior in Image Super-ResolutionCode1
Efficient Real-world Image Super-Resolution Via Adaptive Directional Gradient ConvolutionCode1
Super-Resolving Blurry Images with Events—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified