We propose reliable outdoor object detection on mobile phone imagery from off-the-shelf devices. With the goal to provide both robust object detection and reduction of computation...
This paper addresses view-invariant object detection and pose estimation from a single image. While recent work focuses on object-centered representations of point-based object fe...
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
Tracking a moving person is challenging because a person's appearance in images changes significantly due to articulation, viewpoint changes, and lighting variation across a ...
In this paper, a motion-based approach for detecting highlevel semantic events in video sequences is presented. Its main characteristic is its generic nature, i.e. it can be direc...