Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons
International Journal of Computer Vision
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
The Journal of Machine Learning Research
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Shape Matching and Object Recognition Using Low Distortion Correspondences
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Discovering Objects and their Localization in Images
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
FaceTracer: A Search Engine for Large Collections of Images with Faces
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Towards Scalable Dataset Construction: An Active Learning Approach
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Weakly Supervised Object Localization with Stable Segmentations
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Object Detection with Discriminatively Trained Part-Based Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Sense beauty via face, dressing, and/or voice
Proceedings of the 20th ACM international conference on Multimedia
Hi, magic closet, tell me what to wear!
Proceedings of the 20th ACM international conference on Multimedia
Proceedings of the 20th ACM international conference on Multimedia
Towards measuring the visualness of a concept
Proceedings of the 21st ACM international conference on Information and knowledge management
Attributes for classifier feedback
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Describing clothing by semantic attributes
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Learning hybrid part filters for scene recognition
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Augmented attribute representations
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
What makes a good detector? --- structured priors for learning from few examples
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Discovering a lexicon of parts and attributes
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Unsupervised learning of discriminative relative visual attributes
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Personalized image recommendation and retrieval via latent SVM based model
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Towards decrypting attractiveness via multi-modality cues
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Attribit: content creation with semantic attributes
Proceedings of the 26th annual ACM symposium on User interface software and technology
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It is common to use domain specific terminology - attributes - to describe the visual appearance of objects. In order to scale the use of these describable visual attributes to a large number of categories, especially those not well studied by psychologists or linguists, it will be necessary to find alternative techniques for identifying attribute vocabularies and for learning to recognize attributes without hand labeled training data. We demonstrate that it is possible to accomplish both these tasks automatically by mining text and image data sampled from the Internet. The proposed approach also characterizes attributes according to their visual representation: global or local, and type: color, texture, or shape. This work focuses on discovering attributes and their visual appearance, and is as agnostic as possible about the textual description.