Multiple-instance Learning (MIL) is a new paradigm
of supervised learning that deals with the classification of
bags. Each bag is presented as a collection of instances
from whi...
Zhouyu Fu (Australian National University), Antoni...
Most state-of-the-art nonrigid shape recovery methods
usually use explicit deformable mesh models to regularize
surface deformation and constrain the search space. These
triangu...
Image classification and annotation are important problems
in computer vision, but rarely considered together. Intuitively,
annotations provide evidence for the class label,
and...
Convex and continuous energy formulations for low level
vision problems enable efficient search procedures for the
corresponding globally optimal solutions. In this work we
exte...
Christopher Zach (UNC Chapel Hill), Marc Niethamme...
Latent Variable Models (LVM), like the Shared-GPLVM
and the Spectral Latent Variable Model, help mitigate over-
fitting when learning discriminative methods from small or
modera...