ExpPoint-MAE: Better interpretability and performance for self-supervised point cloud transformers

arXiv:2306.10798v3 Announce Type: replace-cross
Abstract: In this paper we delve into the properties of transformers, attained through self-supervision, in the point cloud domain. Specifically, we evaluate the effectiveness of Masked Autoencoding as a pretraining scheme, and explore Momentum Contrast as an alternative. In our study we investigate the impact of data quantity on the learned features, and uncover similarities in the transformer's behavior across domains. Through comprehensive visualiations, we observe that the transformer learns to attend to semantically meaningful regions, …

abstract arxiv cloud contrast cs.cv cs.lg domain explore impact interpretability paper performance pretraining study supervision through transformers type