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» The Dark Side of Object Learning: Learning Objects
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CVPR
2009
IEEE
15 years 5 months ago
Holistic Context Modeling using Semantic Co-occurrences
We present a simple framework to model contextual relationships between visual concepts. The new framework combines ideas from previous object-centric methods (which model conte...
Nikhil Rasiwasia (University Of California, San Di...
CVPR
2009
IEEE
15 years 5 months ago
Co-training with Noisy Perceptual Observations
Many perception and multimedia indexing problems involve datasets that are naturally comprised of multiple streams or modalities for which supervised training data is only sparsely...
Ashish Kapoor, Chris Mario Christoudias, Raquel Ur...
CVPR
1999
IEEE
15 years 5 days ago
Integrating Shape from Shading and Range Data Using Neural Networks
This paper presents a framework for integrating multiple sensory data, sparse range data and dense depth maps from shape from shading in order to improve the 3D reconstruction of ...
Mostafa G.-H. Mostafa, Sameh M. Yamany, Aly A. Far...
CVPR
2005
IEEE
15 years 5 days ago
Video Epitomes
Recently, "epitomes" were introduced as patch-based probability models that are learned by compiling together a large number of examples of patches from input images. In...
Vincent Cheung, Brendan J. Frey, Nebojsa Jojic
CVPR
2006
IEEE
15 years 5 days ago
A Design Principle for Coarse-to-Fine Classification
Coarse-to-fine classification is an efficient way of organizing object recognition in order to accommodate a large number of possible hypotheses and to systematically exploit shar...
Sachin Gangaputra, Donald Geman