We introduce a variational approach to image segmentation based on sparse coverings of image domains by shape templates. The objective function combines a data term that achieves ...
Dirk Breitenreicher, Jan Lellmann, Christoph Schn&...
“Energy” models for continuous domains can be applied to many problems, but often suffer from high computational expense in training, due to the need to repeatedly minimize t...
We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...
High-level, or holistic, scene understanding involves
reasoning about objects, regions, and the 3D relationships
between them. This requires a representation above the
level of ...
Graph-cuts based algorithms are effective for a variety
of segmentation tasks in computer vision. Ongoing research
is focused toward making the algorithms even more general,
as ...