Fine-tuning vision foundation model for crack segmentation in civil infrastructures

arXiv:2312.04233v3 Announce Type: replace
Abstract: Large-scale foundation models have become the mainstream deep learning method, while in civil engineering, the scale of AI models is strictly limited. In this work, a vision foundation model is introduced for crack segmentation. Two parameter-efficient fine-tuning methods, adapter and low-rank adaptation, are adopted to fine-tune the foundation model in semantic segmentation: the Segment Anything Model (SAM). The fine-tuned CrackSAM shows excellent performance on different scenes and materials. To test the zero-shot performance of the …

abstract adapter ai models arxiv become civil cs.cv deep learning engineering fine-tuning foundation foundation model low low-rank adaptation scale segmentation type vision work