We present a computational framework for the inference of dense descriptions from multiple view stereo with general camera placement. Thus far research on dense multiple view ster...
We address multiple-view reconstruction under an optimization approach based on belief propagation. A novel formulation of belief propagation that operates in 3-D is proposed to f...
E. Scott Larsen, Philippos Mordohai, Marc Pollefey...
Abstract. In this paper, we describe an unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from longterm observations of mo...
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
This paper presents a framework for implicit deformable models and a pair of new algorithms for solving the nonlinear partial di erential equations that result from this framework...