Mixtures of Gaussians are a crucial statistical modeling tool at the heart of many challenging applications in computer vision and machine learning. In this paper, we first descri...
This paper explores the use of alternating sequential patterns of local features and saccading actions to learn robust and compact object representations. The temporal encoding rep...
—Biasing properly the hypothesis space of a learner has been shown to improve generalization performance. Methods for achieving this goal have been proposed, that range from desi...
In this paper, we demonstrate a novel landmark photo search and browsing system, Agate, which ranks landmark image search results considering their relevance, diversity and qualit...
Yuheng Ren, Mo Yu, Xin-Jing Wang, Lei Zhang, Wei-Y...
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...