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CVPR
2009
IEEE
15 years 2 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
CVPR
2011
IEEE
13 years 3 months ago
Learning Object Color Models from Multi-view Constraints
Color is known to be highly discriminative for many object recognition tasks, but is difficult to infer from uncontrolled images in which the illuminant is not known. Traditional...
Trevor Owens, Kate Saenko, Trevor Darrell, Ayan Ch...
SCIA
2005
Springer
174views Image Analysis» more  SCIA 2005»
14 years 1 months ago
Object Localization with Boosting and Weak Supervision for Generic Object Recognition
Abstract. This paper deals, for the first time, with an analysis of localization capabilities of weakly supervised categorization systems. Most existing categorization approaches ...
Andreas Opelt, Axel Pinz
MM
2009
ACM
219views Multimedia» more  MM 2009»
14 years 2 months ago
Descriptive visual words and visual phrases for image applications
The Bag-of-visual Words (BoW) image representation has been applied for various problems in the fields of multimedia and computer vision. The basic idea is to represent images as ...
Shiliang Zhang, Qi Tian, Gang Hua, Qingming Huang,...
DAGM
2008
Springer
13 years 9 months ago
Boosting for Model-Based Data Clustering
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
Amir Saffari, Horst Bischof