We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
We introduce an open data repository and set of associated visualization and analysis tools. The Pittsburgh Science of Learning Center's "DataShop" has data from tho...
Kenneth R. Koedinger, Kyle Cunningham, Alida Skogs...
In this paper we propose a novel computational method to infer visual saliency in images. The method is based on the idea that salient objects should have local characteristics tha...
Combining learning with vision techniques in interactive image retrieval has been an active research topic during the past few years. However, existing learning techniques either ...
In this paper, we tackle the problem of understanding the temporal structure of complex events in highly varying videos obtained from the Internet. Towards this goal, we utilize a...