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 631–640 of 3874 papers

TitleStatusHype
C3-STISR: Scene Text Image Super-resolution with Triple CluesCode1
Lightweight Bimodal Network for Single-Image Super-Resolution via Symmetric CNN and Recursive TransformerCode1
Attentive Fine-Grained Structured Sparsity for Image RestorationCode1
Progressive Training of A Two-Stage Framework for Video RestorationCode1
Deep Model-Based Super-Resolution with Non-uniform BlurCode1
Learn from Unpaired Data for Image Restoration: A Variational Bayes ApproachCode1
A New Dataset and Transformer for Stereoscopic Video Super-ResolutionCode1
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and ResultsCode1
Self-Calibrated Efficient Transformer for Lightweight Super-ResolutionCode1
Edge-enhanced Feature Distillation Network for Efficient Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified