Benchmarking Deep Learning Architectures for Urban Vegetation Point Cloud Semantic Segmentation from MLS

arXiv:2306.10274v3 Announce Type: replace
Abstract: Vegetation is crucial for sustainable and resilient cities providing various ecosystem services and well-being of humans. However, vegetation is under critical stress with rapid urbanization and expanding infrastructure footprints. Consequently, mapping of this vegetation is essential in the urban environment. Recently, deep learning for point cloud semantic segmentation has shown significant progress. Advanced models attempt to obtain state-of-the-art performance on benchmark datasets, comprising multiple classes and representing real world scenarios. However, class specific segmentation with …

abstract architectures arxiv benchmarking cities cloud cs.cv deep learning ecosystem environment however humans infrastructure mapping mls resilient segmentation semantic services stress sustainable type urban