—Object detection is challenging when the object class exhibits large within-class variations. In this work, we show that foreground-background classification (detection) and wit...
Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan ...
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
—Triangulated meshes have become ubiquitous discrete surface representations. In this paper, we address the problem of how to maintain the manifold properties of a surface while ...
—This paper addresses the issue of matching rigid and articulated shapes through probabilistic point registration. The problem is recast into a missing data framework where unkno...
Radu Horaud, Florence Forbes, Manuel Yguel, Guilla...
In some real world applications, such as spectrometry, functional models achieve better predictive performances if they work on the derivatives of order m of their inputs rather t...