Humans have an amazing ability to perceive depth from a single still image; however, it remains a challenging problem for current computer vision systems. In this paper, we will p...
In recent years, matrix approximation for missing value prediction has emerged as an important problem in a variety of domains such as recommendation systems, e-commerce and onlin...
This paper develops a statistical inference approach, Bayesian Tensor Inference, for style transformation between photo images and sketch images of human faces. Motivated by the r...
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Color is of interest to those working in computer vision largely because it is assumed to be helpful for recognition. This assumption has driven much work in color based image ind...