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ACCV
2006
Springer
13 years 11 months ago
Fusion of 3D and Appearance Models for Fast Object Detection and Pose Estimation
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...
Hesam Najafi, Yakup Genc, Nassir Navab
UAI
1996
13 years 7 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
CVPR
2007
IEEE
14 years 7 months ago
Towards Scalable Representations of Object Categories: Learning a Hierarchy of Parts
This paper proposes a novel approach to constructing a hierarchical representation of visual input that aims to enable recognition and detection of a large number of object catego...
Sanja Fidler, Ales Leonardis
IJCNN
2006
IEEE
13 years 11 months ago
Optimal In-Place Learning and the Lobe Component Analysis
— It is difficult to map many existing learning algorithms onto biological networks because the former require a separate learning network. The computational basis of biological...
Juyang Weng, Nan Zhang 0002
DAGM
2010
Springer
13 years 6 months ago
Complex Motion Models for Simple Optical Flow Estimation
The selection of an optical flow method is mostly a choice from among accuracy, efficiency and ease of implementation. While variational approaches tend to be more accurate than lo...
Claudia Nieuwenhuis, Daniel Kondermann, Christoph ...