We present a novel method for the discovery and detection of visual object categories based on decompositions using topic models. The approach is capable of learning a compact and...
Over the last years, object detection has become a more and more active field of research in robotics. An important problem in object detection is the need for sufficient labeled ...
We seek to build a large collection of images with ground truth labels to be used for object detection and recognition research. Such data is useful for supervised learning and qu...
Bryan C. Russell, Antonio Torralba, Kevin P. Murph...
This paper deals with estimation of dense optical flow
and ego-motion in a generalized imaging system by exploiting
probabilistic linear subspace constraints on the flow.
We dea...
Richard Roberts (Georgia Institute of Technology),...
This paper proposes an approach for object class localization which goes beyond bounding boxes, as it also determines the outline of the object. Unlike most current localization m...