PTM: Torus Masking for 3D Representation Learning Guided by Robust and Trusted Teachers

3D Masked Point Modeling (MPM) typically involves randomly or blockly discarding points or patches and then reconstructing them, offering a promising avenue for exploring geometric representation. By surveying current masking strategies, we have found that random-masked regions are provided with exc...

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Veröffentlicht in:	IEEE transactions on circuits and systems for video technology 2024-12, Vol.34 (12), p.12158-12170
Hauptverfasser:	Cheng, Haozhe, Zhu, Jihua, Hu, Naiwen, Chen, Jinqian, Yan, Wenbiao
Format:	Artikel
Sprache:	eng
Schlagworte:	3D point cloud Deep learning evidence deep learning Image reconstruction Image segmentation Knowledge management Masking Modelling Noise measurement Point cloud compression Reconstruction representation learning Representations Residential density Robustness Self-supervised learning self-supervised network Solid modeling Three dimensional models Three-dimensional displays Toruses Uncertainty
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