In many contexts, one is confronted with the problem of extracting information from large amounts of different types soft data (e.g., text) and hard data (from e.g., physics-based...
Thanuka Wickramarathne, Kamal Premaratne, Manohar ...
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...
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
In this paper we present a generative model and learning procedure for unsupervised video clustering into scenes. The work addresses two important problems: realistic modeling of ...
Nemanja Petrovic, Aleksandar Ivanovic, Nebojsa Joj...
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...