Labeling image collections is a tedious task, especially
when multiple labels have to be chosen for each image. In
this paper we introduce a new framework that extends state
of ...
Nicolas Loeff, Ali Farhadi, Ian Endres and David A...
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
Terrains are an essential part of outdoor environments. Terrain models are important for computer games and applications in architecture, urban design and archaeology. A popular a...
Abstract. We consider documents as words and trees on some alphabet and study how to compare them with some regular schemas on an alphabet . Given an input document I, we decide ...
We present here a new descriptor for depth images adapted to 2D/3D model matching and retrieving. We propose a representation of a 3D model by 20 depth images rendered from the ve...