We describe an approach to category-level detection and viewpoint estimation for rigid 3D objects from single 2D images. In contrast to many existing methods, we directly integrat...
Daniel Glasner, Meirav Galun, Sharon Alpert, Ronen...
In this paper, we present a learning procedure called probabilistic boosting network (PBN) for joint real-time object detection and pose estimation. Grounded on the law of total p...
Jingdan Zhang, Shaohua Kevin Zhou, Leonard McMilla...
A new learning strategy for object detection is presented.
The proposed scheme forgoes the need to train a collection
of detectors dedicated to homogeneous families of poses,
an...
Karim Ali, Francois Fleuret, David Hasler and Pasc...
In this paper, a new approach for object detection and pose estimation is introduced. The contribution consists in the conception of entities permitting stable detection and relia...
Stefan Hinterstoisser, Selim Benhimane, Nassir Nav...
Real-time estimation of a camera’s pose relative to an object is still an open problem. The difficulty stems from the need for fast and robust detection of known objects in the s...