The 2005 PASCAL visual object classes challenge

Mark Everingham, Andrew Zisserman, Christopher K. I. Williams, Luc Van Gool, Moray Allan, Christopher M. Bishop, Olivier Chapelle, Navneet Dalal, Thomas Deselaers, Gyuri Dorko, Stefan Duffner, Jan Eichhorn, Jason D. R. Farquhar, Mario Fritz, Christophe Garcia, Tom Griffiths, Frederic Jurie, Daniel Keysers, Markus Koskela, Jorma LaaksonenDiane Larlus, Bastian Leibe, Hongying Meng, Hermann Ney, Bernt Schiele, Cordelia Schmid, Edgar Seemann, John Shawe-Taylor, Amos Storkey, Sandor Szedmak, Bill Triggs, Ilkay Ulusoy, Ville Viitaniemi, Jianguo Zhang

    Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution

    86 Citations (Scopus)


    The PASCAL Visual Object Classes Challenge ran from February to March 2005. The goal of the challenge was to recognize objects from a number of visual object classes in realistic scenes (i.e. not pre-segmented objects). Four object classes were selected: motor-bikes, bicycles, cars and people. Twelve teams entered the challenge. In this chapter we provide details of the datasets, algorithms used by the
    teams, evaluation criteria, and results achieved.
    Original languageEnglish
    Title of host publicationMachine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment
    Subtitle of host publicationFirst PASCAL Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers
    EditorsJoaquin Quinonero-Candela, Ido Dagan, Bernardo Magnini, Florence d'Alche-Buc
    Place of PublicationBerlin
    Number of pages60
    ISBN (Print)9783540334279 , 3540334270
    Publication statusPublished - 2006
    EventFirst PASCAL Machine Learning Challenges Workshop - Southampton, United Kingdom
    Duration: 11 Apr 200513 Apr 2005

    Publication series

    NameLecture notes in computer science


    WorkshopFirst PASCAL Machine Learning Challenges Workshop
    Abbreviated titleMLCW 2005
    Country/TerritoryUnited Kingdom
    Internet address


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