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 1031–1040 of 3874 papers

TitleStatusHype
Discovering Distinctive "Semantics" in Super-Resolution NetworksCode1
Accurate Image Restoration with Attention Retractable TransformerCode1
EFENet: Reference-based Video Super-Resolution with Enhanced Flow EstimationCode1
Enhancing License Plate Super-Resolution: A Layout-Aware and Character-Driven ApproachCode1
Event Enhanced High-Quality Image RecoveryCode1
ERQA: Edge-Restoration Quality Assessment for Video Super-ResolutionCode1
ESRGAN+ : Further Improving Enhanced Super-Resolution Generative Adversarial NetworkCode1
Distribution-Flexible Subset Quantization for Post-Quantizing Super-Resolution NetworksCode1
Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: ReportCode1
Face Hallucination via Split-Attention in Split-Attention NetworkCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified