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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 1–10 of 63 papers

TitleStatusHype
U-Net: Convolutional Networks for Biomedical Image SegmentationCode3
SCSegamba: Lightweight Structure-Aware Vision Mamba for Crack Segmentation in StructuresCode3
Hybrid-Segmentor: A Hybrid Approach to Automated Fine-Grained Crack Segmentation in Civil InfrastructureCode2
Learning-Based Defect Recognitions for Autonomous UAV InspectionsCode2
CrackSegDiff: Diffusion Probability Model-based Multi-modal Crack SegmentationCode1
Crack Segmentation for Low-Resolution Images using Joint Learning with Super-ResolutionCode1
Dual Super-Resolution Learning for Semantic SegmentationCode1
CrackFormer: Transformer Network for Fine-Grained Crack DetectionCode1
CrackNex: a Few-shot Low-light Crack Segmentation Model Based on Retinex Theory for UAV InspectionsCode1
A Convolutional-Transformer Network for Crack Segmentation with Boundary AwarenessCode1
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