Detecting cracks is important in a number of civil engineering applications. Recent advances
in computer vision have enabled automatic crack detection and fine-grained segmentation …

Surface cracks are a common sight on public infrastructure nowadays. Recent work has
been addressing this problem by supporting structural maintenance measures using …

Despite the impressive progress of fully supervised crack segmentation, the tedious pixel-
level annotation restricts its general application. Weakly supervised crack segmentation with …

During the long history of computer vision, one of the grand challenges has been semantic
segmentation which is the ability to segment an unknown image into different parts and …

Semantic segmentation is a challenging task in computer vision. In recent years, the
performance of semantic segmentation has been greatly improved by using deep learning …

The performance of crack segmentation is influenced by complex scenes, including
irregularly shaped cracks, complex image backgrounds, and limitations in acquiring global …

In general, one may have access to a handful of labeled normal and defect datasets. Most
unlabeled datasets contain normal samples because the defect samples occurred rarely …

Crack detection on the outer surface of a nuclear containment to ensure nuclear power plant
safety is an important task. However, as cracks on the surface of nuclear containments are …

Automatic crack segmentation in infrastructure is an important and challenging topic in the
field of computer vision. Cracks on the surface of some infrastructure such as nuclear reactor …

Defect semantic segmentation is a pixel-level inspection technique to guarantee the quality
of various products. It can obtain the precise location of defects by assigning a class label to …