arXiv Open Access 2022

Explaining Hierarchical Features in Dynamic Point Cloud Processing

Pedro Gomes Silvia Rossi Laura Toni

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Abstrak

This paper aims at bringing some light and understanding to the field of deep learning for dynamic point cloud processing. Specifically, we focus on the hierarchical features learning aspect, with the ultimate goal of understanding which features are learned at the different stages of the process and what their meaning is. Last, we bring clarity on how hierarchical components of the network affect the learned features and their importance for a successful learning model. This study is conducted for point cloud prediction tasks, useful for predicting coding applications.

Topik & Kata Kunci

cs.MM

Penulis (3)

Pedro Gomes

Silvia Rossi

Laura Toni

Format Sitasi

APA MLA BibTeX

Gomes, P., Rossi, S., Toni, L. (2022). Explaining Hierarchical Features in Dynamic Point Cloud Processing. https://arxiv.org/abs/2209.15557

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓