Classifying point clouds at the facade-level using geometric features and deep learning networks
<|reference_start|>Classifying point clouds at the facade-level using geometric features and deep learning networks: 3D building models with facade details are playing an important role in many applications now. Classifying point clouds at facade-level is key to create such digital replicas of the real world. However, few studies have focused on such detailed classification with deep neural networks. We propose a method fusing geometric features with deep learning networks for point cloud classification at facade-level. Our experiments conclude that such early-fused features improve deep learning methods' performance. This method can be applied for compensating deep learning networks' ability in capturing local geometric information and promoting the advancement of semantic segmentation.<|reference_end|>
@article{tan2024classifying,
    title={Classifying point clouds at the facade-level using geometric features
  and deep learning networks},
    author={Yue Tan, Olaf Wysocki, Ludwig Hoegner, Uwe Stilla},
    journal={arXiv preprint arXiv:2402.06506},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.06506},
    primaryClass={cs.CV cs.AI cs.LG}
}