CAC: Confidence-Aware Co-Training for Weakly Supervised Crack Segmentation
Fengjiao Liang,
Qingyong Li,
Xiaobao Li
et al.
Abstract:Automatic crack segmentation plays an essential role in maintaining the structural health of buildings and infrastructure. Despite the success in fully supervised crack segmentation, the costly pixel-level annotation restricts its application, leading to increased exploration in weakly supervised crack segmentation (WSCS). However, WSCS methods inevitably bring in noisy pseudo-labels, which results in large fluctuations. To address this problem, we propose a novel confidence-aware co-training (CAC) framework f… Show more
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