Common Sense Understanding

My research tries to bring common sense understanding to robotic perception. Interacting with the environment requires to perceive objects and understand how actions influence their movement ad shape.

Generative perception models can make sense of partial and noisy observations and reconstruct their shape and semantics (Hu et al., 2021), (Hu et al., 2020), (Yang et al., 2018), .

Understanding the intuitive physics of interacting with objects will provide next-generation automonous agents with a common sense knowledge base for interacting with a complex, dynamic environment (Wang et al., 2018), (Wang et al., 2018), (Wang et al., 2018) .

References

2021

  1. randlanet-tpami.jpg
    Learning semantic segmentation of large-scale point clouds with random sampling
    Qingyong Hu, Bo Yang, Linhai Xie , and 5 more authors
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021

2020

  1. randlanet.gif
    Randla-net: Efficient semantic segmentation of large-scale point clouds
    Qingyong Hu, Bo Yang, Linhai Xie , and 5 more authors
    In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2020

2018

  1. 3d-dense-tpami.jpg
    Dense 3D object reconstruction from a single depth view
    Bo Yang, Stefano Rosa, Andrew Markham , and 2 more authors
    IEEE transactions on pattern analysis and machine intelligence, 2018
  2. intphys-neurips.png
    Learning the intuitive physics of non-rigid object deformations
    Zhihua Wang, Stefano Rosa, and Andrew Markham
    In Neural Information Processing Systems (NIPS) Workshops , 2018
  3. 3dphysnet.gif
    3d-physnet: Learning the intuitive physics of non-rigid object deformations
    Zhihua Wang, Stefano Rosa, Bo Yang , and 3 more authors
    In Proceedings of the 27th International Joint Conference on Artificial Intelligence, Stockholm, SWE , 2018
  4. defonet.jpg
    Defo-Net: Learning body deformation using generative adversarial networks
    Zhihua Wang, Stefano Rosa, Linhai Xie , and 4 more authors
    In 2018 IEEE International Conference on Robotics and Automation (ICRA) , 2018