In this paper, we introduce a new approach for modeling
visual context. For this purpose, we consider the leaves of a
hierarchical segmentation tree as elementary units. Each
le...
Joseph J. Lim, Pablo Arbelaez, Chunhui Gu, and Jit...
We present a method to classify and localize human actions in video using a Hough transform voting framework. Random trees are trained to learn a mapping between densely-sampled f...
We present a method for detecting and parsing buildings from unorganized 3D point clouds into a compact, hierarchical representation that is useful for high-level tasks. The input...
We present Apatite, a new tool that aids users in learning and understanding a complex API by visualizing the common associations between its various components. Current object-or...
Daniel S. Eisenberg, Jeffrey Stylos, Brad A. Myers
Abstract—We introduce and validate Spatiotemporal Relational Random Forests, which are random forests created with spatiotemporal relational probability trees. We build on the do...
Timothy A. Supinie, Amy McGovern, John Williams, J...