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Geodesic convolutional neural networks o...

Masci, Jonathan...

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Geodesic convolutional neural networks on Riemannian manifolds by Masci, Jonathan ( Author )

Content Provider	Lemonjar Open Access
Publisher	Australian National University
Publication Date	07-09-2023
Summary	Feature descriptors play a crucial role in a wide range of geometry analysis and processing applications, including shape correspondence, retrieval, and segmentation. In this paper, we introduce Geodesic Convolutional Neural Networks (GCNN), a generalization of the convolutional networks (CNN) paradigm to non-Euclidean manifolds. Our construction is based on a local geodesic system of polar coordinates to extract "patches", which are then passed through a cascade of filters and linear and non-linear operators. The coefficients of the filters and linear combination weights are optimization variables that are learned to minimize a task-specific cost function. We use GCNN to learn invariant shape features, allowing to achieve state-of-the-art performance in problems such as shape description, retrieval, and correspondence.
ISBN	-
Item Type	Article
File Type	pdf
File Size	29.34 KB
Language	English
Subjects	-
Unlimited	MYR 0.01
Total read	-
URL	http://arxiv.org/abs/1501.06297

Citation

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AMA 11th EditionReferences

Masci, Jonathan. Geodesic convolutional neural networks on Riemannian manifolds. Australian National University. September 07, 2023. Accessed November 01, 2024. https://online.provdatabase.com/cite/24286

APA 7th EditionReferences

Masci, Jonathan. (2023). Geodesic convolutional neural networks on Riemannian manifolds. Australian National University. https://online.provdatabase.com/cite/24286

Chicago 17th EditionReferences

Masci, Jonathan. Geodesic convolutional neural networks on Riemannian manifolds. Australian National University. 2023. https://online.provdatabase.com/cite/24286

HarvardReferences

Masci, Jonathan. (2023). Geodesic convolutional neural networks on Riemannian manifolds. [Online]. Australian National University. Available from: https://online.provdatabase.com/cite/24286. (Accessed 01 November 2024).

Harvard AustraliaReferences

Masci, Jonathan, 2023, Geodesic convolutional neural networks on Riemannian manifolds, Australian National University, viewed 01 November 2024, <https://online.provdatabase.com/cite/24286>

MLA 9th EditionWorks Cited

Masci, Jonathan. Geodesic convolutional neural networks on Riemannian manifolds. Australian National University, 2023. PROV Database, https://online.provdatabase.com/cite/24286.

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