Advancements in Point Cloud Data Augmentation for Deep Learning: A Survey. (arXiv:2308.12113v3 [cs.CV] UPDATED)

Deep learning (DL) has become one of the mainstream and effective methods for
point cloud analysis tasks such as detection, segmentation and classification.
To reduce overfitting during training DL models and improve model performance
especially when the amount and/or diversity of training data are limited,
augmentation is often crucial. Although various point cloud data augmentation
methods have been widely used in different point cloud processing tasks, there
are currently no published systematic surveys or reviews of these methods.
Therefore, this …

analysis arxiv augmentation become classification cloud cloud data cs.cv data deep learning detection diversity overfitting performance reduce segmentation survey tasks training training data