Crack Segmentation
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Benchmarks
CrackVision12K
Most implemented
U-Net: Convolutional Networks for Biomedical Image Segmentation
Fully Convolutional Networks for Semantic Segmentation
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
Training-Free Decoding of SAM3 Semantic Responses for Cross-Domain Infrastructure Crack Segmentation
Papers
Compass: Degradation-Simulated Reciprocal Learning with Lightweight Needle RWKV for Multimodal Crack Segmentation under Missing Modalities
In multimodal crack segmentation for industrial facilities, the key challenge is preventing missing modalities from degrading pixel-level performance while maintaining low computational cost. Existing methods struggle to…
Crack SegmentationTraining-Free Decoding of SAM3 Semantic Responses for Cross-Domain Infrastructure Crack Segmentation
Cross-domain infrastructure crack segmentation is challenged by variations in materials, imaging conditions, crack morphology, and background interference. Although text-promptable foundation models reduce the need for t…
Crack SegmentationRethinking Efficient Crack Segmentation with Task-Aligned Structural-Directional Modeling
Recent crack segmentation methods often follow generic semantic segmentation designs, using stronger backbones, hybrid CNN-Transformer-Mamba encoders, and auxiliary enhancement branches. Although effective, this raises w…
Semantic SegmentationCrack SegmentationSCRWKV: Ultra-Compact Structure-Calibrated Vision-RWKV for Topological Crack Segmentation
Achieving pixel-level accurate segmentation of structural cracks across diverse scenarios remains a formidable challenge. Existing methods face significant bottlenecks in balancing crack topology modeling with computatio…
Computational EfficiencyCrack SegmentationUnGAP: Uncertainty-Guided Affine Prompting for Real-Time Crack Segmentation
Real-time crack segmentation is vital for structural health monitoring but is plagued by aleatoric uncertainties arising from varying lighting, blur, and texture ambiguity. Current uncertainty-aware approaches typically …
Object SegmentationCrack SegmentationCrackForward: Context-Aware Severity Stage Crack Synthesis for Data Augmentation
Reliable crack detection and segmentation are vital for structural health monitoring, yet the scarcity of well-annotated data constitutes a major challenge. To address this limitation, we propose a novel context-aware ge…
Crack SegmentationData Augmentation