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ICML
1997
IEEE
14 years 5 months ago
Learning Belief Networks in the Presence of Missing Values and Hidden Variables
In recent years there has been a flurry of works on learning probabilistic belief networks. Current state of the art methods have been shown to be successful for two learning scen...
Nir Friedman
PAMI
2011
12 years 7 months ago
Hidden Part Models for Human Action Recognition: Probabilistic versus Max Margin
—We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden condi...
Yang Wang 0003, Greg Mori
EMMCVPR
2007
Springer
13 years 10 months ago
Compositional Object Recognition, Segmentation, and Tracking in Video
Abstract. The complexity of visual representations is substantially limited by the compositional nature of our visual world which, therefore, renders learning structured object mod...
Björn Ommer, Joachim M. Buhmann
DAGM
2010
Springer
13 years 2 months ago
3D Reconstruction Using an n-Layer Heightmap
We present a novel method for 3D reconstruction of urban scenes extending a recently introduced heightmap model. Our model has several advantages for 3D modeling of urban scenes: i...
David Gallup, Marc Pollefeys, Jan-Michael Frahm
AAAI
2010
13 years 6 months ago
Efficient Lifting for Online Probabilistic Inference
Lifting can greatly reduce the cost of inference on firstorder probabilistic graphical models, but constructing the lifted network can itself be quite costly. In online applicatio...
Aniruddh Nath, Pedro Domingos