Connecting Touch and Vision via Cross-Modal Prediction

@article{Li2019ConnectingTA,
  title={Connecting Touch and Vision via Cross-Modal Prediction},
  author={Yunzhu Li and Jun-Yan Zhu and Russ Tedrake and Antonio Torralba},
  journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2019},
  pages={10601-10610}
}
  • Yunzhu Li, Jun-Yan Zhu, A. Torralba
  • Published 1 June 2019
  • Computer Science
  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Humans perceive the world using multi-modal sensory inputs such as vision, audition, and touch. In this work, we investigate the cross-modal connection between vision and touch. The main challenge in this cross-domain modeling task lies in the significant scale discrepancy between the two: while our eyes perceive an entire visual scene at once, humans can only feel a small region of an object at any given moment. To connect vision and touch, we introduce new tasks of synthesizing plausible… 

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