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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. ...
ICCV
2009
IEEE
14 years 11 months ago
Which Faces to Tag: Adding Prior Constraints into Active Learning
We introduce an algorithm that guides the user to tag faces in the best possible order during a face recognition assisted tagging scenario. In particular, we extend the active l...
Ashish Kapoor, Gang Hua, Amir Akbarzadeh and Simon...
ICCV
2005
IEEE
14 years 8 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
ICMCS
2005
IEEE
90views Multimedia» more  ICMCS 2005»
13 years 11 months ago
Eye Detection Under Unconstrained Background by the Terrain Feature
Locating eyes in face images is an important step for automatic face analysis and recognition. In this paper, we present a novel approach for eye detection without finding the fa...
Jun Wang, Lijun Yin
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 6 months ago
Probabilistic author-topic models for information discovery
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...