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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 1–50 of 63 papers

TitleStatusHype
SCSegamba: Lightweight Structure-Aware Vision Mamba for Crack Segmentation in StructuresCode3
U-Net: Convolutional Networks for Biomedical Image SegmentationCode3
Hybrid-Segmentor: A Hybrid Approach to Automated Fine-Grained Crack Segmentation in Civil InfrastructureCode2
Learning-Based Defect Recognitions for Autonomous UAV InspectionsCode2
Topology-aware Mamba for Crack Segmentation in StructuresCode1
CrackSegDiff: Diffusion Probability Model-based Multi-modal Crack SegmentationCode1
IRFusionFormer: Enhancing Pavement Crack Segmentation with RGB-T Fusion and Topological-Based LossCode1
Staircase Cascaded Fusion of Lightweight Local Pattern Recognition and Long-Range Dependencies for Structural Crack SegmentationCode1
Mamba meets crack segmentationCode1
Segmentation tool for images of cracksCode1
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
CrackFormer: Transformer Network for Fine-Grained Crack DetectionCode1
Crack Detection as a Weakly-Supervised Problem: Towards Achieving Less Annotation-Intensive Crack DetectorsCode1
Dual Super-Resolution Learning for Semantic SegmentationCode1
Fully Convolutional Networks for Semantic SegmentationCode1
Automatic Classification and Segmentation of Tunnel Cracks Based on Deep Learning and Visual Explanations—0
On-Device Crack Segmentation for Edge Structural Health Monitoring—0
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM—0
Cracks in concrete—0
Context-CrackNet: A Context-Aware Framework for Precise Segmentation of Tiny Cracks in Pavement images—0
CrossDiff: Diffusion Probabilistic Model With Cross-conditional Encoder-Decoder for Crack Segmentation—0
Unified Few-shot Crack Segmentation and its Precise 3D Automatic Measurement in Concrete Structures—0
CrackUDA: Incremental Unsupervised Domain Adaptation for Improved Crack Segmentation in Civil Structures—0
CrackESS: A Self-Prompting Crack Segmentation System for Edge Devices—0
DSCformer: A Dual-Branch Network Integrating Enhanced Dynamic Snake Convolution and SegFormer for Crack Segmentation—0
Multi-temporal crack segmentation in concrete structure using deep learning approaches—0
Deep Learning-Based Fatigue Cracks Detection in Bridge Girders using Feature Pyramid Networks—0
Benefiting from Quantum? A Comparative Study of Q-Seg, Quantum-Inspired Techniques, and U-Net for Crack Segmentation—0
Distribution-aware Noisy-label Crack SegmentationCode0
EfficientCrackNet: A Lightweight Model for Crack Segmentation—0
Vision Mamba-based autonomous crack segmentation on concrete, asphalt, and masonry surfaces—0
Robust feature knowledge distillation for enhanced performance of lightweight crack segmentation models—0
Deep Learning for Segmentation of Cracks in High-Resolution Images of Steel Bridges—0
A statistical method for crack detection in 3D concrete images—0
Mind Marginal Non-Crack Regions: Clustering-Inspired Representation Learning for Crack Segmentation—0
Fine-tuning vision foundation model for crack segmentation in civil infrastructures—0
Designing a Hybrid Neural System to Learn Real-world Crack Segmentation from Fractal-based Simulation—0
Infrastructure Crack Segmentation: Boundary Guidance Method and Benchmark DatasetCode0
TrueDeep: A systematic approach of crack detection with less data—0
Dual flow fusion model for concrete surface crack segmentation—0
A Few-Shot Attention Recurrent Residual U-Net for Crack SegmentationCode0
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