We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
We present an approach to high-level shape editing that adapts the structure of the shape while maintaining its global characteristics. Our main contribution is a new algebraic mo...
Martin Bokeloh, Michael Wand, Hans-Peter Seidel, V...
We combine the strengths of Bayesian modeling and synchronous grammar in unsupervised learning of basic translation phrase pairs. The structured space of a synchronous grammar is ...
Hao Zhang, Chris Quirk, Robert C. Moore, Daniel Gi...
High-throughput, data-directed computational protocols for Structural Genomics (or Proteomics) are required in order to evaluate the protein products of genes for structure and fu...
We consider a class of learning problems that involve a structured sparsityinducing norm defined as the sum of -norms over groups of variables. Whereas a lot of effort has been pu...