This paper presents a practical technique to automatically compute approximations of polygonal representations of 3D objects. It is based on a previously developed model simplific...
We propose an approach for learning visual models of object categories in an unsupervised manner in which we first build a large-scale complex network which captures the interacti...
How can knowing about some categories help us to discover new ones in unlabeled images? Unsupervised visual category discovery is useful to mine for recurring objects without huma...
In performing most everyday tasks, we use information from several different sensory modalities, yet our understanding of how these inputs are integrated is limited. The present s...
Gayla L. Poling, Janet M. Weisenberger, Thomas Ker...
In this paper, we present a generative model for textured motion phenomena, such as falling snow, wavy river and dancing grass, etc. Firstly, we represent an image as a linear sup...