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» Latent Layout Analysis for Discovering Objects in Images
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ICIP
2007
IEEE
14 years 1 months ago
Modeling vs. Segmenting Images Using A Probabilistic Approach
Image segmentation is conventionally formulated as a pixellabeling problem, in which “hard” decisions have to be made to partition pixels into regions. As image segmentation i...
Datong Chen
CVPR
2011
IEEE
13 years 5 months ago
Learning Better Image Representations Using 'Flobject Analysis'
Unsupervised learning can be used to extract image representations that are useful for various and diverse vision tasks. After noticing that most biological vision systems for int...
Inmar Givoni, Patrick Li, Brendan Frey
CVPR
2007
IEEE
14 years 9 months ago
A Topic-Motion Model for Unsupervised Video Object Discovery
The bag-of-words representation has attracted a lot of attention recently in the field of object recognition. Based on the bag-of-words representation, topic models such as Probab...
David Liu, Tsuhan Chen
CVPR
2012
IEEE
11 years 10 months ago
Automatic discovery of groups of objects for scene understanding
Objects in scenes interact with each other in complex ways. A key observation is that these interactions manifest themselves as predictable visual patterns in the image. Discoveri...
Congcong Li, Devi Parikh, Tsuhan Chen
ICCV
2007
IEEE
14 years 9 months ago
How Good are Local Features for Classes of Geometric Objects
Recent work in object categorization often uses local image descriptors such as SIFT to learn and detect object categories. Such descriptors explicitly code local appearance and h...
Michael Stark, Bernt Schiele