Deep Learning for Computer Graphics and Geometry Processing
Date
2019Author
Guibas, Leonidas
Kokkinos, Iasonas
Litany, Or
Mitra, Niloy
Monti, Federico
Metadata
Show full item recordAbstract
In computer graphics and geometry processing, many traditional problems are now becoming increasingly handled by data-driven methods. In an increasing variety of problem settings, deep networks are state-of-the-art, beating dedicated hand-crafted methods by significant margins. This tutorial gives an organized overview of core theory, practice, and graphics-related applications of deep learning.
BibTeX
@inproceedings {10.2312:egt.20191036,
booktitle = {Eurographics 2019 - Tutorials},
editor = {Jakob, Wenzel and Puppo, Enrico},
title = {{Deep Learning for Computer Graphics and Geometry Processing}},
author = {Bronstein, Michael and Guibas, Leonidas and Kokkinos, Iasonas and Litany, Or and Mitra, Niloy and Monti, Federico and Rodolà, Emanuele},
year = {2019},
publisher = {The Eurographics Association},
ISSN = {1017-4656},
DOI = {10.2312/egt.20191036}
}
booktitle = {Eurographics 2019 - Tutorials},
editor = {Jakob, Wenzel and Puppo, Enrico},
title = {{Deep Learning for Computer Graphics and Geometry Processing}},
author = {Bronstein, Michael and Guibas, Leonidas and Kokkinos, Iasonas and Litany, Or and Mitra, Niloy and Monti, Federico and Rodolà, Emanuele},
year = {2019},
publisher = {The Eurographics Association},
ISSN = {1017-4656},
DOI = {10.2312/egt.20191036}
}