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» Learning the Compositional Nature of Visual Objects
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ICCV
2009
IEEE
16 years 2 months ago
Active Skeleton for Non-rigid Object Detection
We present a shape-based algorithm for detecting and recognizing non-rigid objects from natural images. The existing literature in this domain often cannot model the objects ver...
Xiang Bai, Xinggang Wang, Longin Jan Latecki, Weny...
86
Voted
PRL
2007
101views more  PRL 2007»
14 years 9 months ago
Accuracy versus speed in context-based object detection
The visual detection and recognition of objects is facilitated by context. This paper studies two types of learning methods for realizing context-based object detection in paintin...
Niek Bergboer, Eric O. Postma, H. Jaap van den Her...
CVPR
2009
IEEE
16 years 4 months ago
Unsupervised Learning of Hierarchical Spatial Structures In Images
The visual world demonstrates organized spatial patterns, among objects or regions in a scene, object-parts in an object, and low-level features in object-parts. These classes o...
Devi Parikh (Carnegie Mellon University), C. Lawre...
AAAI
2008
14 years 12 months ago
Learning to Connect Language and Perception
To truly understand language, an intelligent system must be able to connect words, phrases, and sentences to its perception of objects and events in the world. Current natural lan...
Raymond J. Mooney
85
Voted
HRI
2006
ACM
15 years 3 months ago
FOCUS: a generalized method for object discovery for robots that observe and interact with humans
The essence of the signal-to-symbol problem consists of associating a symbolic description of an object (e.g., a chair) to a signal (e.g., an image) that captures the real object....
Manuela M. Veloso, Paul E. Rybski, Felix von Hunde...