Machine Learning - Special issue on inductive transfer
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Cross-Generalization: Learning Novel Classes from a Single Example by Feature Replacement
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Learning Hierarchical Models of Scenes, Objects, and Parts
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Learning Object Categories from Google"s Image Search
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
One-Shot Learning of Object Categories
IEEE Transactions on Pattern Analysis and Machine Intelligence
Separating Style and Content with Bilinear Models
Neural Computation
Incremental learning of object detectors using a visual shape alphabet
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
LabelMe: A Database and Web-Based Tool for Image Annotation
International Journal of Computer Vision
80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
Semi-Supervised Learning
Sharing features: efficient boosting procedures for multiclass object detection
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Multiple region categorization for scenery images
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
Video semantic concept detection using ontology
Proceedings of the Third International Conference on Internet Multimedia Computing and Service
On the pooling of positive examples with ontology for visual concept learning
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Event detection and scene attraction by very simple contextual cues
J-MRE '11 Proceedings of the 2011 joint ACM workshop on Modeling and representing events
Improving video classification via youtube video co-watch data
SBNMA '11 Proceedings of the 2011 ACM workshop on Social and behavioural networked media access
Attributes for classifier feedback
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Improving image distance metric learning by embedding semantic relations
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
Relative forest for attribute prediction
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Thinking of images as what they are: compound matrix regression for image classification
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Theoretical aspects of mapping to multidimensional optimal regions as a multi-classifier
Intelligent Data Analysis
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In an object recognition scenario with tens of thousands of categories, even a small number of labels per category leads to a very large number of total labels required. We propose a simple method of label sharing between semantically similar categories. We leverage the WordNet hierarchy to define semantic distance between any two categories and use this semantic distance to share labels. Our approach can be used with any classifier. Experimental results on a range of datasets, upto 80 million images and 75,000 categories in size, show that despite the simplicity of the approach, it leads to significant improvements in performance.