computational-label-and-data-efficiency-in-deep-learning-for-sparse-3d-data.pdf

Deep learning is widely applied to sparse 3D data to perform challenging tasks, e.g., 3D object detection and semantic segmentation. However, the high performance of deep learning comes with high costs, including computational costs and the effort to capture and label data. This work investigates an...

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Γλώσσα:English
Έκδοση: KIT Scientific Publishing 2024
Διαθέσιμο Online:https://doi.org/10.5445/KSP/1000168541
Περιγραφή
Περίληψη:Deep learning is widely applied to sparse 3D data to perform challenging tasks, e.g., 3D object detection and semantic segmentation. However, the high performance of deep learning comes with high costs, including computational costs and the effort to capture and label data. This work investigates and improves the efficiency of deep learning for sparse 3D data to overcome the obstacles to the further development of this technology.