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Crack Segmentation

Crack segmentation in computer vision involves identifying and delineating cracks or fractures in various types of surfaces, such as roads, pavements, walls, or infrastructure. This task is crucial for infrastructure maintenance, as it helps in assessing the condition of structures and planning repairs.

Papers

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Showing 11–20 of 63 papers

TitleStatusHype
CrackNex: a Few-shot Low-light Crack Segmentation Model Based on Retinex Theory for UAV InspectionsCode1
UP-CrackNet: Unsupervised Pixel-Wise Road Crack Detection via Adversarial Image RestorationCode1
Real-time High-Resolution Neural Network with Semantic Guidance for Crack SegmentationCode1
Joint Learning of Blind Super-Resolution and Crack Segmentation for Realistic Degraded ImagesCode1
A Convolutional-Transformer Network for Crack Segmentation with Boundary AwarenessCode1
CrackSeg9k: A Collection and Benchmark for Crack Segmentation Datasets and FrameworksCode1
Local Intensity Order Transformation for Robust Curvilinear Object SegmentationCode1
Weakly-Supervised Surface Crack Segmentation by Generating Pseudo-Labels using Localization with a Classifier and ThresholdingCode1
Crack Segmentation for Low-Resolution Images using Joint Learning with Super-ResolutionCode1
SegFormer: Simple and Efficient Design for Semantic Segmentation with TransformersCode1
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