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» Efficient, Feature-based, Conditional Random Field Parsing
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CVIU
2006
222views more  CVIU 2006»
13 years 6 months ago
Conditional models for contextual human motion recognition
We present algorithms for recognizing human motion in monocular video sequences, based on discriminative Conditional Random Field (CRF) and Maximum Entropy Markov Models (MEMM). E...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
UAI
2004
13 years 8 months ago
From Fields to Trees
We present new MCMC algorithms for computing the posterior distributions and expectations of the unknown variables in undirected graphical models with regular structure. For demon...
Firas Hamze, Nando de Freitas
IR
2006
13 years 6 months ago
Table extraction for answer retrieval
The ability to find tables and extract information from them is a necessary component of many information retrieval tasks. Documents often contain tables in order to communicate d...
Xing Wei, W. Bruce Croft, Andrew McCallum
ICASSP
2010
IEEE
13 years 7 months ago
Discriminative template extraction for direct modeling
This paper addresses the problem of developing appropriate features for use in direct modeling approaches to speech recognition, such as those based on Maximum Entropy models or S...
Shankar Shivappa, Patrick Nguyen, Geoffrey Zweig
ICPR
2010
IEEE
13 years 10 months ago
Efficient Learning to Label Images
Conditional random field methods (CRFs) have gained popularity for image labeling tasks in recent years. In this paper, we describe an alternative discriminative approach, by exte...
Ke Jia, Li Cheng, Nianjun Liu, Lei Wang