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» Automatic link detection: a sequence labeling approach
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NIPS
2001
13 years 10 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
CPAIOR
2008
Springer
13 years 10 months ago
A Novel Approach For Detecting Symmetries in CSP Models
Abstract. While several powerful methods exist for automatically detecting symmetries in instances of constraint satisfaction problems (CSPs), current methods for detecting symmetr...
Christopher Mears, Maria J. García de la Ba...
ACL
2012
11 years 11 months ago
Automatic Event Extraction with Structured Preference Modeling
This paper presents a novel sequence labeling model based on the latent-variable semiMarkov conditional random fields for jointly extracting argument roles of events from texts. ...
Wei Lu, Dan Roth
IVC
2002
185views more  IVC 2002»
13 years 8 months ago
Path detection in video surveillance
This paper addresses the problem of automatically extracting frequently used pedestrian pathways from video sequences of natural outdoor scenes. Path models are learnt from the ac...
Dimitrios Makris, Tim Ellis
CVPR
2010
IEEE
14 years 5 months ago
Automatic Discovery of Meaningful Object Parts with Latent CRFs
Object recognition is challenging due to high intra-class variability caused, e.g., by articulation, viewpoint changes, and partial occlusion. Successful methods need to strike a...
Paul Schnitzspan, Stefan Roth, Bernt Schiele