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» Learning Syntactic Verb Frames using Graphical Models
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HRI
2010
ACM
14 years 5 days ago
Toward understanding natural language directions
—Speaking using unconstrained natural language is an intuitive and flexible way for humans to interact with robots. Understanding this kind of linguistic input is challenging be...
Thomas Kollar, Stefanie Tellex, Deb Roy, Nicholas ...
ICCV
2005
IEEE
13 years 11 months ago
Learning Hierarchical Models of Scenes, Objects, and Parts
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
BMVC
2010
13 years 3 months ago
Label propagation in complex video sequences using semi-supervised learning
We propose a novel directed graphical model for label propagation in lengthy and complex video sequences. Given hand-labelled start and end frames of a video sequence, a variation...
Ignas Budvytis, Vijay Badrinarayanan, Roberto Cipo...
TIP
2008
86views more  TIP 2008»
13 years 5 months ago
Learning the Dynamics and Time-Recursive Boundary Detection of Deformable Objects
We propose a principled framework for recursively segmenting deformable objects across a sequence of frames. We demonstrate the usefulness of this method on left ventricular segmen...
Walter Sun, Müjdat Çetin, Raymond C. C...
COLING
2008
13 years 6 months ago
An Integrated Probabilistic and Logic Approach to Encyclopedia Relation Extraction with Multiple Features
We propose a new integrated approach based on Markov logic networks (MLNs), an effective combination of probabilistic graphical models and firstorder logic for statistical relatio...
Xiaofeng Yu, Wai Lam