PittsburghV1, France, Analysis, bibRecord, 000779

Dataset issues in object recognition

Identifieur interne : 000779 ( France/Analysis ); précédent : 000778; suivant : 000780

Dataset issues in object recognition

Auteurs : Jean Ponce [États-Unis] ; Tamara Berg [États-Unis] ; Mark Everingham [Royaume-Uni] ; David Forsyth [États-Unis] ; Martial Hebert [États-Unis] ; Svetlana Lazebnik [États-Unis] ; Marcin Marszałek [France] ; Cordelia Schmid [France] ; Bryan Russell [États-Unis] ; Antonio Torralba [États-Unis] ; Chris Williams [Royaume-Uni] ; Jianguo Zhang [France] ; Andrew Zisserman [Royaume-Uni]

Source :

RBID : Hal:inria-00548595

Abstract

Appropriate datasets are required at all stages of object recognition research, including learning visual models of object and scene categories, detecting and localizing instances of these models in images, and evaluating the performance of recognition algorithms. Current datasets are lacking in several respects, and this paper discusses some of the lessons learned from existing efforts, as well as innovative ways to obtain very large and diverse annotated datasets. It also suggests a few criteria for gathering future datasets.

Url:

https://hal.inria.fr/inria-00548595

Affiliations:

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Hal:inria-00548595

Le document en format XML

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<author><name sortKey="Zisserman, Andrew" sort="Zisserman, Andrew" uniqKey="Zisserman A" first="Andrew" last="Zisserman">Andrew Zisserman</name>
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          <desc>            <address>              <addrLine>Information Engineering Building Oxford University</addrLine>
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<front><div type="abstract" xml:lang="en">Appropriate datasets are required at all stages of object recognition research, including learning visual models of object and scene categories, detecting and localizing instances of these models in images, and evaluating the performance of recognition algorithms. Current datasets are lacking in several respects, and this paper discusses some of the lessons learned from existing efforts, as well as innovative ways to obtain very large and diverse annotated datasets. It also suggests a few criteria for gathering future datasets.</div>
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<li>Massachusetts</li>
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<tree><country name="États-Unis"><noRegion><name sortKey="Ponce, Jean" sort="Ponce, Jean" uniqKey="Ponce J" first="Jean" last="Ponce">Jean Ponce</name>
</noRegion>
<name sortKey="Berg, Tamara" sort="Berg, Tamara" uniqKey="Berg T" first="Tamara" last="Berg">Tamara Berg</name>
<name sortKey="Forsyth, David" sort="Forsyth, David" uniqKey="Forsyth D" first="David" last="Forsyth">David Forsyth</name>
<name sortKey="Hebert, Martial" sort="Hebert, Martial" uniqKey="Hebert M" first="Martial" last="Hebert">Martial Hebert</name>
<name sortKey="Lazebnik, Svetlana" sort="Lazebnik, Svetlana" uniqKey="Lazebnik S" first="Svetlana" last="Lazebnik">Svetlana Lazebnik</name>
<name sortKey="Russell, Bryan" sort="Russell, Bryan" uniqKey="Russell B" first="Bryan" last="Russell">Bryan Russell</name>
<name sortKey="Torralba, Antonio" sort="Torralba, Antonio" uniqKey="Torralba A" first="Antonio" last="Torralba">Antonio Torralba</name>
</country>
<country name="Royaume-Uni"><noRegion><name sortKey="Everingham, Mark" sort="Everingham, Mark" uniqKey="Everingham M" first="Mark" last="Everingham">Mark Everingham</name>
</noRegion>
<name sortKey="Williams, Chris" sort="Williams, Chris" uniqKey="Williams C" first="Chris" last="Williams">Chris Williams</name>
<name sortKey="Zisserman, Andrew" sort="Zisserman, Andrew" uniqKey="Zisserman A" first="Andrew" last="Zisserman">Andrew Zisserman</name>
</country>
<country name="France"><region name="Auvergne-Rhône-Alpes"><name sortKey="Marszalek, Marcin" sort="Marszalek, Marcin" uniqKey="Marszalek M" first="Marcin" last="Marszałek">Marcin Marszałek</name>
</region>
<name sortKey="Schmid, Cordelia" sort="Schmid, Cordelia" uniqKey="Schmid C" first="Cordelia" last="Schmid">Cordelia Schmid</name>
<name sortKey="Zhang, Jianguo" sort="Zhang, Jianguo" uniqKey="Zhang J" first="Jianguo" last="Zhang">Jianguo Zhang</name>
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Dataset issues in object recognition

Dataset issues in object recognition

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