ExpPoint-MAE: Better Interpretability and Performance for Self-Supervised Point Cloud Transformers

ExpPoint-MAE: Better Interpretability and Performance for Self-Supervised Point Cloud Transformers

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 impac...

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Bibliographic Details
Main Authors: Ioannis Romanelis, Vlassis Fotis, Konstantinos Moustakas, Adrian Munteanu
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Deep learning
explainability
point clouds
self-supervision
transformers
Online Access:https://ieeexplore.ieee.org/document/10497601/

Internet

https://ieeexplore.ieee.org/document/10497601/

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