Multi-source Domain Adaptation for Unsupervised Road Defect Segmentation
Jongmin Yu,Hyeontaek Oh,Sebastiano Fichera,Paolo Paoletti,Shan Luo,Jongmin Yu,Hyeontaek Oh,Sebastiano Fichera,Paolo Paoletti,Shan Luo
The performance of road defect segmentation (a.k.a. pixel-level road defect detection) has been improved alongside with remarkable achievement of deep learning. Those improvements need a large-scale and well-constructed dataset. However, road surface materials or designs vary from country to country, and the patterns of defects are hard to pre-define. In this paper, we propose a novel multi-source...
