In this paper we describe a novel technique which implements a spatiotemporal model as a set of sub-models based on first order logic. These sub-models model different, typicall...
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...
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
We propose a two-class classification model for grouping. Human segmented natural images are used as positive examples. Negative examples of grouping are constructed by randomly m...
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...