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 151–160 of 3874 papers

TitleStatusHype
Enhanced Semantic Extraction and Guidance for UGC Image Super ResolutionCode1
Global and Local Mamba Network for Multi-Modality Medical Image Super-Resolution—0
VibrantLeaves: A principled parametric image generator for training deep restoration modelsCode0
The Tenth NTIRE 2025 Efficient Super-Resolution Challenge ReportCode3
PG-DPIR: An efficient plug-and-play method for high-count Poisson-Gaussian inverse problems—0
ContrastiveGaussian: High-Fidelity 3D Generation with Contrastive Learning and Gaussian SplattingCode0
Event Signal Filtering via Probability Flux Estimation—0
PIDSR: Complementary Polarized Image Demosaicing and Super-ResolutionCode1
MoEDiff-SR: Mixture of Experts-Guided Diffusion Model for Region-Adaptive MRI Super-ResolutionCode1
From Specificity to Generality: Revisiting Generalizable Artifacts in Detecting Face Deepfakes—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified