Landmark labeling of training images is essential for many learning tasks in computer vision, such as object detection, tracking, and alignment. Image labeling is typically conduc...
Yan Tong, Xiaoming Liu 0002, Frederick W. Wheeler,...
Abstract. The aim of this paper is to learn driving behaviour by associating the actions recorded from a human driver with pre-attentive visual input, implemented using holistic im...
We consider the problem of parsing facial features from an image labeling perspective. We learn a per-pixel unary classifier, and a prior over expected label configurations, allow...
This paper addresses Named Entity Mining (NEM), in which we mine knowledge about named entities such as movies, games, and books from a huge amount of data. NEM is potentially use...
We propose a framework for large scale learning and annotation of structured models. The system interleaves interactive labeling (where the current model is used to semiautomate t...