Incremental Crowd-Source Data Fusion and Map Update Method Based on Driving Data for Traffic Signs

The accessibility of building function is essential for urban research. We reviewed the recent work and concluded three limitations: few open-source datasets, coarse building function categories, and poor model interpretability with inadequate multimodal feature fusion. Thus, we created BuildingSense with fine-grained categories and multimodal data, and proved that the large model can be used for improving the interpretability of results, with three directions for enhancing their performance.