Corpus ID: 7587278

Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning

@inproceedings{Wu2015GalileoPP,
  title={Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning},
  author={Jiajun Wu and Ilker Yildirim and Joseph J. Lim and Bill Freeman and Joshua B. Tenenbaum},
  booktitle={NIPS},
  year={2015}
}
  • Jiajun Wu, Ilker Yildirim, +2 authors Joshua B. Tenenbaum
  • Published in NIPS 2015
  • Computer Science
  • Humans demonstrate remarkable abilities to predict physical events in dynamic scenes, and to infer the physical properties of objects from static images. We propose a generative model for solving these problems of physical scene understanding from real-world videos and images. At the core of our generative model is a 3D physics engine, operating on an object-based representation of physical properties, including mass, position, 3D shape, and friction. We can infer these latent properties using… CONTINUE READING

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