A challenging problem of multi-label learning is that both the label space and the model complexity will grow rapidly with the increase in the number of labels, and thus makes the...
We address the problem of finding the most likely assignment or MAP estimation in a Markov random field. We analyze the linear programming formulation of MAP through the lens of...
Abstract— We consider a wireless broadcast station that transmits packets to multiple users. The packet requests for each user may overlap, and some users may already have certai...
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
—This paper presents a robust and automatic approach to photometric stereo, where the two main components, namely surface normals and visible surfaces, are respectively optimized...