@Article{Guadarrama_2013_16450,
  author = {Guadarrama, S. and Krishnamoorthy, N. and Malkarnenkar, G. and Venugopalan, S. and Mooney, R. and Darrell, T. and Saenko, K.},
 booktitle = {Proceedings of the IEEE International Conference on Computer Vision},
 journal = {Proceedings of the IEEE International Conference on Computer Vision},
 month = {dec},
 pages = {2712-2719},
 title = {Youtube2text: recognizing and describing arbitrary activities using semantic hierarchies and zero-shot recognition},
 year = {2013},
 issn = {1550-5499},
 keywords = {natural language processing;object recognition;social networking (online);text analysis;Web-scale natural language corpora;YouTube2Text;actor-action-object combination penalization;arbitrary activity description;arbitrary activity recognition;generalization level;large YouTube corpus;large-scale object recognition;out-of-domain actions;pragmatic standpoint;pretrained model;semantic hierarchy learning;short-sentence description generation;training set;verbs;video activity;video clips;zero-shot recognition;Accuracy;Predictive models;Semantics;Support vector machines;Training;Visualization;YouTube;Describing Activities in videos;Large-scale activity recognition;Recognizing activities in videos;semantic hierarchies;zero-shot learning},
 doi = {10.1109/ICCV.2013.337},
 title_with_no_special_chars = {YouTube2Text Recognizing and Describing Arbitrary Activities Using Semantic Hierarchies and ZeroShot Recognition}
}

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