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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