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ICCV
2009
IEEE
13 years 3 months ago
Unsupervised learning of high-order structural semantics from images
Structural semantics are fundamental to understanding both natural and man-made objects from languages to buildings. They are manifested as repeated structures or patterns and are...
Jizhou Gao, Yin Hu, Jinze Liu, Ruigang Yang
CVPR
2007
IEEE
14 years 3 days ago
Unsupervised Learning of Hierarchical Semantics of Objects (hSOs)
A successful representation of objects in the literature is as a collection of patches, or parts, with a certain appearance and position. The relative locations of the different p...
Devi Parikh, Tsuhan Chen
ICIP
2006
IEEE
14 years 7 months ago
Unsupervised Image Layout Extraction
We propose a novel unsupervised learning algorithm to extract the layout of an image by learning latent object-related aspects. Unlike traditional image segmentation algorithms th...
David Liu, Datong Chen, Tsuhan Chen
NIPS
2004
13 years 7 months ago
Modeling Nonlinear Dependencies in Natural Images using Mixture of Laplacian Distribution
Capturing dependencies in images in an unsupervised manner is important for many image processing applications. We propose a new method for capturing nonlinear dependencies in ima...
Hyun-Jin Park, Te-Won Lee
MM
2005
ACM
209views Multimedia» more  MM 2005»
13 years 11 months ago
Learning an image-word embedding for image auto-annotation on the nonlinear latent space
Latent Semantic Analysis (LSA) has shown encouraging performance for the problem of unsupervised image automatic annotation. LSA conducts annotation by keywords propagation on a l...
Wei Liu, Xiaoou Tang