The 2005 PASCAL visual object classes challenge

被引：0

作者：

Everingham, Mark ^{[1
]}

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, Ilkay

Viitaniemi, Ville

Zhang, Jianguo

机构：

[1] Univ Oxford, Oxford, England

[2] Univ Edinburgh, Edinburgh, Midlothian, Scotland

[3] ETH Zentrum, Zurich, Switzerland

[4] Rhein Westfal TH Aachen, Aachen, Germany

[5] Tech Univ Darmstadt, D-64287 Darmstadt, Germany

[6] France Telecom, Cesson Sevigne, France

[7] Aalto Univ, Helsinki, Finland

[8] INRIA Rhone Alpes, Montbonnot St Martin, France

[9] Middle E Tech Univ, TR-06531 Ankara, Turkey

[10] Microsoft Res, Cambridge, England

[11] Max Planck Inst Biol Cybernet, Tubingen, Germany

[12] Univ Southampton, Southampton, Hants, England

来源：

MACHINE LEARNING CHALLENGES: EVALUATING PREDICTIVE UNCERTAINTY VISUAL OBJECT CLASSIFICATION AND RECOGNIZING TEXTUAL ENTAILMENT | 2006年 / 3944卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：117 / 176

页数：60

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