Mitra, NJ;
Kokkinos, I;
Guerrero, P;
Thuerey, N;
Kim, V;
Guibas, L;
(2019)
CreativeAI: Deep learning for graphics SIGGRAPH 2019.
In:
Proceeding SIGGRAPH '19 ACM.
ACM: Los Angeles, California.
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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.
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