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 281–290 of 3874 papers

TitleStatusHype
AdaDM: Enabling Normalization for Image Super-ResolutionCode1
Cascaded Temporal Updating Network for Efficient Video Super-ResolutionCode1
Cross-sensor super-resolution of irregularly sampled Sentinel-2 time seriesCode1
CADyQ: Content-Aware Dynamic Quantization for Image Super-ResolutionCode1
A Benchmark for Chinese-English Scene Text Image Super-resolutionCode1
C3-STISR: Scene Text Image Super-resolution with Triple CluesCode1
CABM: Content-Aware Bit Mapping for Single Image Super-Resolution Network with Large InputCode1
Component Divide-and-Conquer for Real-World Image Super-ResolutionCode1
Deep Video Super-Resolution using HR Optical Flow EstimationCode1
BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable AlignmentCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified