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A survey on deep geometry learning: From a representation perspective

A survey on deep geometry learning: From a representation perspective

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_2e50939e12e14dffad73adec5cb777f8

A survey on deep geometry learning: From a representation perspective

About this item

Full title

A survey on deep geometry learning: From a representation perspective

Publisher

Beijing: Tsinghua University Press

Journal title

Computational Visual Media, 2020-06, Vol.6 (2), p.113-133

Language

English

Formats

Publication information

Publisher

Beijing: Tsinghua University Press

More information

Scope and Contents

Contents

Researchers have achieved great success in dealing with 2D images using deep learning. In recent years, 3D computer vision and geometry deep learning have gained ever more attention. Many advanced techniques for 3D shapes have been proposed for different applications. Unlike 2D images, which can be uniformly represented by a regular grid of pixels,...

Alternative Titles

Full title

A survey on deep geometry learning: From a representation perspective

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_2e50939e12e14dffad73adec5cb777f8

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_2e50939e12e14dffad73adec5cb777f8

Other Identifiers

ISSN

2096-0433

E-ISSN

2096-0662

DOI

10.1007/s41095-020-0174-8

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