Weighted point cloud augmentation for neural network training data class-imbalance

A key issue when training deep neural networks for outdoor point clouds is the inevitable large data imbalance. For example, a typical street scene will contain orders of magnitudes more ground points than street furniture. We develop a novel solution to apply a weighted augmentation to physically decrease the class-imbalance.

People

• David Griffiths
• Prof. Jan Boehm

Publication

Publisher link