In this paper we address the problem of recognising interactions between two people in realistic scenarios for video retrieval purposes. We develop a per-person descriptor that us...
Alonso Patron, Marcin Marszalek, Andrew Zisserman,...
We explore an approach to 3D people tracking with learned motion models and deterministic optimization. The tracking problem is formulated as the minimization of a differentiable ...
Abstract: Transactional network data can be thought of as a list of oneto-many communications (e.g., email) between nodes in a social network. Most social network models convert th...
Interactive3Dlearningenvironmentscanproviderichproblemsolving experiences with unparalleled visual impact. In these environments, students interactively solve problems by directin...
William H. Bares, Luke S. Zettlemoyer, Dennis W. R...
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...