Many problems in vision involve the prediction of a class label for each frame in an unsegmented sequence. In this paper, we develop a discriminative framework for simultaneous se...
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
The paper has two main contributions: The rst is a set of methods for computing structure and motion for m 3 views of 6 points. It is shown that a geometric image error can be mini...
Frederik Schaffalitzky, Andrew Zisserman, Richard ...
Ontology summarization is very important to quick understanding and selection of ontologies. In this paper, we study extractive summarization of ontology. We propose a notion of R...
Data quality is a critical problem in modern databases. Data entry forms present the first and arguably best opportunity for detecting and mitigating errors, but there has been li...
Kuang Chen, Harr Chen, Neil Conway, Joseph M. Hell...