

“This is a challenging but interesting generative task with the potential to assist and expand content creations in arts and sports, such as a theatrical performance, rhythmic gymnastics, and figure skating,” NVIDIA stated in a paper on the subject.
This deep learning method is based on a decomposition-to-composition framework. That’s to say, the GAN learns how to move from the data its fed, and then how to compose dance moves on its own. It may sound simple, but there is a lot involved here—the resulting dance moves the GAN comes up have to match the type of music being played, stay in beat, and look natural.
“Extensive qualitative and quantitative evaluations demonstrate that the synthesized dances by the proposed method are not only realistic and diverse but also style-consistent and beat-matching,” the researchers stated in their paper.
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