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CreativeAI: Deep learning for graphics SIGGRAPH 2019

  • Niloy J. Mitra
  • , Iasonas Kokkinos
  • , Paul Guerrero
  • , Nils Thuerey
  • , Vladimir Kim
  • , Leonidas Guibas
  • UCL
  • Adobe Research
  • Stanford University

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

4 Zitate (Scopus)

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.

OriginalspracheEnglisch
TitelACM SIGGRAPH 2019 Courses, SIGGRAPH 2019
Herausgeber (Verlag)Association for Computing Machinery, Inc
ISBN (elektronisch)9781450363075
DOIs
PublikationsstatusVeröffentlicht - 28 Juli 2019
VeranstaltungACM SIGGRAPH 2019 Courses - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2019 - Los Angeles, USA/Vereinigte Staaten
Dauer: 28 Juli 2019 → …

Publikationsreihe

NameACM SIGGRAPH 2019 Courses, SIGGRAPH 2019

Konferenz

KonferenzACM SIGGRAPH 2019 Courses - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2019
Land/GebietUSA/Vereinigte Staaten
OrtLos Angeles
Zeitraum28/07/19 → …

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