TY - GEN
T1 - CreativeAI
T2 - ACM SIGGRAPH 2019 Courses - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2019
AU - Mitra, Niloy J.
AU - Kokkinos, Iasonas
AU - Guerrero, Paul
AU - Thuerey, Nils
AU - Kim, Vladimir
AU - Guibas, Leonidas
N1 - Publisher Copyright:
© 2019 Copyright held by the owner/author(s).
PY - 2019/7/28
Y1 - 2019/7/28
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85071429543&partnerID=8YFLogxK
U2 - 10.1145/3305366.3328059
DO - 10.1145/3305366.3328059
M3 - Conference contribution
AN - SCOPUS:85071429543
T3 - ACM SIGGRAPH 2019 Courses, SIGGRAPH 2019
BT - ACM SIGGRAPH 2019 Courses, SIGGRAPH 2019
PB - Association for Computing Machinery, Inc
Y2 - 28 July 2019
ER -