LabelMe: A Database and Web-Based Tool for Image Annotation
International Journal of Computer Vision
From Aardvark to Zorro: A Benchmark for Mammal Image Classification
International Journal of Computer Vision
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Image retrieval ++--web image retrieval with an enhanced multi-modality ontology
Multimedia Tools and Applications
A survey of methods for image annotation
Journal of Visual Languages and Computing
Photo-based question answering
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Ontology enhanced web image retrieval: aided by wikipedia & spreading activation theory
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Towards Scalable Dataset Construction: An Active Learning Approach
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Modeling and Recognition of Landmark Image Collections Using Iconic Scene Graphs
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Edge Detection from Global and Local Views Using an Ensemble of Multiple Edge Detectors
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Mining the web for visual concepts
Proceedings of the 9th International Workshop on Multimedia Data Mining: held in conjunction with the ACM SIGKDD 2008
LS-MMRM '09 Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining
LS-MMRM '09 Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining
Coboost learning of visual categories with 1st and 2nd order features from Google images
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Semi-supervised learning of visual classifiers from web images and text
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Filter object categories: employing visual consistency and semi-supervised approach
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Improving image sets through sense disambiguation and context ranking
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Automatic online labeling images via co-active-learning
Proceedings of the First International Conference on Internet Multimedia Computing and Service
Tag dictionary and its applications
Proceedings of the international conference on Multimedia information retrieval
OPTIMOL: Automatic Online Picture Collection via Incremental Model Learning
International Journal of Computer Vision
Filter object categories using coboost with 1st and 2nd order features
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Two-stage localization for image labeling
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
Automatic attribute discovery and characterization from noisy web data
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Semantic label sharing for learning with many categories
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Weakly supervised landmark labeling in searched data
ICIMCS '10 Proceedings of the Second International Conference on Internet Multimedia Computing and Service
Multiple hypergraph clustering of web images by mining Word2Image correlations
Journal of Computer Science and Technology
Learning to re-rank: query-dependent image re-ranking using click data
Proceedings of the 20th international conference on World wide web
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Modeling and Recognition of Landmark Image Collections Using Iconic Scene Graphs
International Journal of Computer Vision
Multi-class object layout with unsupervised image classification and object localization
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Content quality based image retrieval with multiple instance boost ranking
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Face Recognition from Caption-Based Supervision
International Journal of Computer Vision
Joint-rerank: a novel method for image search reranking
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Apples to oranges: evaluating image annotations from natural language processing systems
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Semantic based retrieval system of arctic animal images
Proceedings of the 1st ACM international workshop on Multimedia analysis for ecological data
Joint image and word sense discrimination for image retrieval
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
Learning realistic facial expressions from web images
Pattern Recognition
VISOR: towards on-the-fly large-scale object category retrieval
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
"Tell me more": how semantic technologies can help refining internet image search
Proceedings of the International Workshop on Video and Image Ground Truth in Computer Vision Applications
Cross-modal alignment for wildlife recognition
Proceedings of the 2nd ACM international workshop on Multimedia analysis for ecological data
Multimedia search reranking: A literature survey
ACM Computing Surveys (CSUR)
The Visual Computer: International Journal of Computer Graphics
A Multi-View Embedding Space for Modeling Internet Images, Tags, and Their Semantics
International Journal of Computer Vision
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We demonstrate a method for identifying images containing categories of animals. The images we classify depict animals in a wide range of aspects, configurations and appearances. In addition, the images typically portray multiple species that differ in appearance (e.g. ukari's, vervet monkeys, spider monkeys, rhesus monkeys, etc.). Our method is accurate despite this variation and relies on four simple cues: text, color, shape and texture. Visual cues are evaluated by a voting method that compares local image phenomena with a number of visual exemplars for the category. The visual exemplars are obtained using a clustering method applied to text on web pages. The only supervision required involves identifying which clusters of exemplars refer to which sense of a term (for example, "monkey" can refer to an animal or a bandmember). Because our method is applied to web pages with free text, the word cue is extremely noisy. We show unequivocal evidence that visual information improves performance for our task. Our method allows us to produce large, accurate and challenging visual datasets mostly automatically.