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» Learning a Sparse Representation for Object Detection
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MLDM
2005
Springer
15 years 3 months ago
Unsupervised Learning of Visual Feature Hierarchies
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
Fabien Scalzo, Justus H. Piater
CVPR
2012
IEEE
13 years 2 days ago
Pose pooling kernels for sub-category recognition
The ability to normalize pose based on super-category landmarks can significantly improve models of individual categories when training data are limited. Previous methods have co...
Ning Zhang, Ryan Farrell, Trevor Darrell
88
Voted
FGR
2008
IEEE
264views Biometrics» more  FGR 2008»
14 years 11 months ago
Large scale learning and recognition of faces in web videos
The phenomenal growth of video on the web and the increasing sparseness of meta information associated with it forces us to look for signals from the video content for search/info...
Ming Zhao 0003, Jay Yagnik, Hartwig Adam, David Ba...
EMMCVPR
2011
Springer
13 years 9 months ago
High Resolution Segmentation of Neuronal Tissues from Low Depth-Resolution EM Imagery
The challenge of recovering the topology of massive neuronal circuits can potentially be met by high throughput Electron Microscopy (EM) imagery. Segmenting a 3-dimensional stack o...
Daniel Glasner, Tao Hu, Juan Nunez-Iglesias, Lou S...
ECCV
2006
Springer
15 years 11 months ago
Learning Compositional Categorization Models
Abstract. This contribution proposes a compositional approach to visual object categorization of scenes. Compositions are learned from the Caltech 101 database1 intermediate abstra...
Björn Ommer, Joachim M. Buhmann