Unsupervised Learning for Physical Interaction through Video Prediction

  title={Unsupervised Learning for Physical Interaction through Video Prediction},
  author={Chelsea Finn and Ian J. Goodfellow and Sergey Levine},
A core challenge for an agent learning to interact with the world is to predict how its actions affect objects in its environment. Many existing methods for learning the dynamics of physical interactions require labeled object information. However, to scale real-world interaction learning to a variety of scenes and objects, acquiring labeled data becomes increasingly impractical. To learn about physical object motion without labels, we develop an action-conditioned video prediction model that… CONTINUE READING
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