In computer graphics, many traditional problems are now better handled by deep-learning based 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.

Previous versions of this course have been presented at Eurographics 2018, Siggraph Asia 2018, and to be presented at Siggraph 2019, websites for these courses are available here:
Eurographics 2018
Siggraph Asia 2018
Siggraph 2019


Code

github.com/smartgeometry-ucl/dl4g


Slides


BibTex

            @inproceedings{Bronstein:2019:CDL,
            author = {Bronstein, Michael and Guibas, Leonidas and Kokkinos, Iasonas and Litany, Or  and Mitra, Niloy and Monti, Federico and RodolĂ , Emanuele},
            title = {CreativeAI: Deep Learning for Graphics},
            booktitle = {Eurographics 2019 Tutorials},
            series = {Eurographics Tutorials},
            year = {2019},
            isbn = {},
            location = {},
            pages = {},
            articleno = {},
            numpages = {},
            url = {},
            doi = {},
            acmid = {},
            }