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Results 1 - 10
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196,621
Parameter Estimation in Learning Object Class Models
"... The aim of the project is to learn and recognize object class models from unlabelled and unsegmented cluttered images based on the maximum likelihood unsupervised learning approach suggested by Weber et al [2,3]. The focus is on learning, in which the parameters of the object model are estimated usi ..."
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The aim of the project is to learn and recognize object class models from unlabelled and unsegmented cluttered images based on the maximum likelihood unsupervised learning approach suggested by Weber et al [2,3]. The focus is on learning, in which the parameters of the object model are estimated
Discriminative object class models of appearance and shape by correlatons
- In IEEE Computer Vision and Pattern Recognition
, 2006
"... This paper presents a new model of object classes which incorporates appearance and shape information jointly. Modeling objects appearance by distributions of visual words has recently proven successful. Here appearancebased models are augmented by capturing the spatial arrangement of visual words. ..."
Abstract
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Cited by 78 (1 self)
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This paper presents a new model of object classes which incorporates appearance and shape information jointly. Modeling objects appearance by distributions of visual words has recently proven successful. Here appearancebased models are augmented by capturing the spatial arrangement of visual words
Efficient learning of relational object class models
- In ICCV
, 2005
"... We present an efficient method for learning part-based object class models. The models include part appearance, as well as location and scale relations between parts. The object class is generatively modeled using a simple Bayesian network with a central hidden node containing location and scale inf ..."
Abstract
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Cited by 26 (7 self)
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We present an efficient method for learning part-based object class models. The models include part appearance, as well as location and scale relations between parts. The object class is generatively modeled using a simple Bayesian network with a central hidden node containing location and scale
Object class recognition by unsupervised scale-invariant learning
- In CVPR
, 2003
"... We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constellations of parts. A probabilistic representation is used for all aspects of the object: shape, appearance, occlusion and ..."
Abstract
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Cited by 1127 (50 self)
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We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constellations of parts. A probabilistic representation is used for all aspects of the object: shape, appearance, occlusion
Efficient Learning of Relational Object Class Models
"... We present an efficient method for learning part-based object class models. The models include location and scale relations between parts, as well as part appearance. Models are learnt from raw object and background images, represented as an unordered set of features extracted using an interest poin ..."
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We present an efficient method for learning part-based object class models. The models include location and scale relations between parts, as well as part appearance. Models are learnt from raw object and background images, represented as an unordered set of features extracted using an interest
A shape-based object class model for knowledge transfer
- In Twelfth IEEE International Conference on Computer Vision (ICCV
, 2009
"... Object class models trained on hundreds or thousands of images have shown to enable robust detection. Transferring knowledge from such models to new object classes trained from a few or even as little as one training instance however is still in its infancy. This paper designs a shape-based model th ..."
Abstract
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Cited by 51 (5 self)
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Object class models trained on hundreds or thousands of images have shown to enable robust detection. Transferring knowledge from such models to new object classes trained from a few or even as little as one training instance however is still in its infancy. This paper designs a shape-based model
Hierarchical Models of Object Recognition in Cortex
, 1999
"... The classical model of visual processing in cortex is a hierarchy of increasingly sophisticated representations, extending in a natural way the model of simple to complex cells of Hubel and Wiesel. Somewhat surprisingly, little quantitative modeling has been done in the last 15 years to explore th ..."
Abstract
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Cited by 836 (84 self)
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the biological feasibility of this class of models to explain higher level visual processing, such as object recognition. We describe a new hierarchical model that accounts well for this complex visual task, is consistent with several recent physiological experiments in inferotemporal cortex and makes testable
Object Detection with Discriminatively Trained Part Based Models
"... We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-of-the-art results in the PASCAL object detection challenges. While deformable part models have become quite popular, their ..."
Abstract
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Cited by 1422 (49 self)
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We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-of-the-art results in the PASCAL object detection challenges. While deformable part models have become quite popular
Refactoring Object-Oriented Frameworks
, 1992
"... This thesis defines a set of program restructuring operations (refactorings) that support the design, evolution and reuse of object-oriented application frameworks. The focus of the thesis is on automating the refactorings in a way that preserves the behavior of a program. The refactorings are defin ..."
Abstract
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Cited by 489 (4 self)
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, for some cases it can be determined whether these refactorings can be applied safely. Three of the most complex refactorings are defined in detail: generalizing the inheritance hierarchy, specializing the inheritance hierarchy and using aggregations to model the relationships among classes
The 2005 pascal visual object classes challenge
, 2006
"... Abstract. The PASCAL Visual Object Classes Challenge ran from February to March 2005. The goal of the challenge was to recognize objects from a number of visual object classes in realistic scenes (i.e. not pre-segmented objects). Four object classes were selected: motorbikes, bicycles, cars and peop ..."
Abstract
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Cited by 649 (23 self)
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Abstract. The PASCAL Visual Object Classes Challenge ran from February to March 2005. The goal of the challenge was to recognize objects from a number of visual object classes in realistic scenes (i.e. not pre-segmented objects). Four object classes were selected: motorbikes, bicycles, cars
Results 1 - 10
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196,621
