Ubisoft's Low-Cost Deep Learning Model for Natural Character Movement

Have a look at a system developed by a research team from Ubisoft in France and Concordia University in the United States, The team developed a deep learning model for in-game character animation that allows developers to automatically generate natural character animation reducing time costs.

Motion Matching involves a simple yet powerful way of animating characters in games. "Compared to other methods, it doesn’t require very much manual work once you have a basic set-up: there is no need to structure clips in graphs, to carefully cut or synchronize them, or to explicitly create new transitions between states," noted the team.

Unlike other similar approaches. Learned Motion Matching, which leverages Machine Learning, allows developers to drastically reduce the memory usage of Motion Matching based animation systems using new algorithmics.

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