3 accepted papers
Crack segmentation datasets make great efforts to obtain the ground truth crack or non-crack labels as clearly as possible. However it can be observed that ambiguities are still inevitable when considering the marginal non-crack region due to low contrast and heterogeneous texture. To solve this pro…
Cracks are usually curve-like structures that are the focus of many computer-vision applications (e.g., road safety inspection and surface inspection of industrial facilities). The existing pixel-based crack segmentation methods rely on time-consuming and costly pixel-level annotations. And the obje…
Despite the substantial progress of deep models for crack recognition, due to the inconsistent cracks in varying sizes, shapes, and noisy background textures, there still lacks the discriminative power of the deeply learned features when supervised by the cross-entropy loss. In this paper, we propos…