• Speaker: Huaiwei Cong
  • Date: 10:00 A.M., Friday, Jul 29, 2016
  • Place: Room 1022

This paper propose to represent a geometric 3D shape as a probability distribution of binary variables on a 3D voxel grid, using a Convolutional Deep Belief Network.


[1] N. Atanasov, B. Sankaran, J. Le Ny, T. Koletschka, G. J.
Pappas, and K. Daniilidis. Hypothesis testing framework for
active object detection. In ICRA, 2013.
[2] N. Atanasov, B. Sankaran, J. L. Ny, G. J. Pappas, and
K. Daniilidis. Nonmyopic view planning for active object
detection. arXiv preprint arXiv:1309.5401, 2013. 3
[3] M. Attene. A lightweight approach to repairing digitized
polygon meshes. The Visual Computer, 2010.
[4] P. J. Besl and N. D. McKay. Method for registration of 3-d
shapes. In PAMI, 1992.
[5] I. Biederman. Recognition-by-components: a theory of human
image understanding. Psychological review, 1987.

Last Modified: 2016/07/29 12:10 | Author: NICA