CreativeAI: Deep learning for graphics SIGGRAPH 2019

Niloy J. Mitra, Iasonas Kokkinos, Paul Guerrero, Nils Thuerey, Vladimir Kim, Leonidas Guibas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In computer graphics, many traditional problems are now better handled by deep-learning based data-driven methods. In applications that operate on regular 2D domains, like image processing and computational photography, deep networks are state-of-the-art, often beating dedicated hand-crafted methods by significant margins. More recently, other domains such as geometry processing, animation, video processing, and physical simulations have benefited from deep learning methods as well, often requiring application-specific learning architectures. The massive volume of research that has emerged in just a few years is often difficult to grasp for researchers new to this area. This course gives an organized overview of core theory, practice, and graphics-related applications of deep learning.

Original languageEnglish
Title of host publicationACM SIGGRAPH 2019 Courses, SIGGRAPH 2019
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450363075
DOIs
StatePublished - 28 Jul 2019
EventACM SIGGRAPH 2019 Courses - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2019 - Los Angeles, United States
Duration: 28 Jul 2019 → …

Publication series

NameACM SIGGRAPH 2019 Courses, SIGGRAPH 2019

Conference

ConferenceACM SIGGRAPH 2019 Courses - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2019
Country/TerritoryUnited States
CityLos Angeles
Period28/07/19 → …

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