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» Learning Mid-Level Features For Recognition
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CVPR
2008
IEEE
14 years 9 months ago
Action recognition by learning mid-level motion features
This paper presents a method for human action recognition based on patterns of motion. Previous approaches to action recognition use either local features describing small patches...
Alireza Fathi, Greg Mori
ACL
2008
13 years 9 months ago
Exploiting Feature Hierarchy for Transfer Learning in Named Entity Recognition
We present a novel hierarchical prior structure for supervised transfer learning in named entity recognition, motivated by the common structure of feature spaces for this task acr...
Andrew Arnold, Ramesh Nallapati, William W. Cohen
CVPR
2007
IEEE
14 years 9 months ago
Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Fabien Scalzo, Justus H. Piater
ICANN
2005
Springer
14 years 1 months ago
Learning Features of Intermediate Complexity for the Recognition of Biological Motion
Humans can recognize biological motion from strongly impoverished stimuli, like point-light displays. Although the neural mechanism underlying this robust perceptual process have n...
Rodrigo Sigala, Thomas Serre, Tomaso Poggio, Marti...
FGR
2008
IEEE
208views Biometrics» more  FGR 2008»
14 years 2 months ago
Unsupervised learning from local features for video-based face recognition
This paper presents an unsupervised learning approach to video-based face recognition that does not make any assumptions about the pose, expressions or prior localization of landm...
Ajmal Mian