Depth ordering is instrumental for understanding the 3D geometry of an image. We as humans are surprisingly good ordering even with abstract 2D line drawings. In this paper we pro...
Zhaoyin Jia, Andrew C. Gallagher, Yao-Jen Chang, T...
In this paper, we propose a unified graphical-model framework to interpret a scene composed of multiple objects in monocular video sequences. Using a single pairwise Markov random...
Neural networks are a popular technique for learning the adaptive control of non-linear plants. When applied to the complex control of android robots, however, they suffer from se...
Heni Ben Amor, Shuhei Ikemoto, Takashi Minato, Ber...
This paper presents a framework for a learning based approach to dynamically evolve the conceptual structure of a database in order to facilitate virtual representation of data in ...
Second-order priors on the smoothness of 3D surfaces are a better model of typical scenes than first-order priors. However, stereo reconstruction using global inference algorithm...
Oliver J. Woodford, Philip H. S. Torr, Ian D. Reid...