| Overview: |
This talk will present a 4-year line of research applying deep learning for character animation and control, and discuss what has been learned creating realistic character movements from motion capture data. It will cover several examples of interactive character control, including quadruped locomotion, character-scene interactions, basketball plays and martial arts movements, and how one piece of work led to the next application, problem and solution. Several video examples of different motion skills will be showcased, and what is key to making AI-powered systems successfully learn and generate high-quality character movements with neural networks, as relevant for developers, artists or researchers working in the games industry.
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