We address the problem of unsupervised learning of complex articulated object models from 3D range data. We describe an algorithm whose input is a set of meshes corresponding to d...
We consider the problem of classification of multiple observations of the same object, possibly under different transformations. We view this problem as a special case of semi-sup...
Machine learning with few training examples always leads to over-fitting problems, whereas human individuals are often able to recognize difficult object categories from only one ...
The primary objective of this research work is to develop an efficient and intuitive deformation technique for virtual human modeling by silhouettes input. With our method, the re...
Charlie C. L. Wang, Yu Wang 0010, Matthew Ming-Fai...
Despite the recent proliferation of work on semistructured data models, there has been little work to date on supporting uncertainty in these models. In this paper, we propose a m...