Computational, Label, and Data Efficiency in Deep Learning for Sparse 3D Data

Beschreibung

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.

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Lanxiao Li

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Deep Learning Künstliche Intelligenz 3D-Daten Effizienz Deep Learning Artificial Intelligence 3D Data Efficiency

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