  Symmetry detection has been a classical problem in computer graphics, many of
which using traditional geometric methods. In recent years, however, we have
witnessed the arising deep learning changed the landscape of computer graphics.
In this paper, we aim to solve the symmetry detection of the occluded point
cloud in a deep-learning fashion. To the best of our knowledge, we are the
first to utilize deep learning to tackle such a problem. In such a deep
learning framework, double supervisions: points on the symmetry plane and
normal vectors are employed to help us pinpoint the symmetry plane. We
conducted experiments on the YCB- video dataset and demonstrate the efficacy of
our method.
