The 2005 PASCAL visual object classes challenge

Date

2006-01-01

Author

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

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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: motorbikes, 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.

Subject Keywords

Image, Scale, Receiver operating characteristic curve, Visual word, Detection task, Average precision, Interest point

URI

https://hdl.handle.net/11511/54685

Journal

MACHINE LEARNING CHALLENGES

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

M. Everingham et al., “The 2005 PASCAL visual object classes challenge,” MACHINE LEARNING CHALLENGES, pp. 117–176, 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54685.