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Computing / Imaging / Vision / Object / Minimum bounding box / Collision detection / Bounding volume / Image processing / Computer vision / Segmentation


Efficient Object Localization and Segmentation in Weakly Labeled Videos Mrigank Rochan and Yang Wang Department of Computer Science, University of Manitoba, Canada {mrochan, ywang}@cs.umanitoba.ca
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Document Date: 2014-11-01 14:35:12


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File Size: 4,62 MB

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City

Bruce / /

Company

YouTube / built using YouTube-Objects dataset / /

Currency

pence / /

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Facility

University of Manitoba / University of Manitoba Research Grants Program / /

IndustryTerm

Web-scale Vision / method aeroplane bird boat car / video retrieval algorithms / segmentation algorithm / web-scale video / car cat cow dog horse bike train total / frank-wolfe algorithm / localization algorithm / Internet videos / search results / /

Organization

Weakly Labeled Videos Mrigank Rochan and Yang Wang Department of Computer Science / University of Manitoba / University of Manitoba Research Grants Program / U.S. Securities and Exchange Commission / Pattern Analysis and Machine Intelligence / NSERC / /

Person

Wang Fig / Yang Wang / Van Gool / /

Position

representative / /

Product

Edge Boxes / GrabCut / /

ProvinceOrState

North Dakota / /

PublishedMedium

IEEE Transactions on Pattern Analysis and Machine Intelligence / ACM Transactions on Graphics / Lecture Notes in Computer Science / /

Technology

frank-wolfe algorithm / segmentation algorithm / GrabCut algorithm / video retrieval algorithms / Boxes algorithm / localization algorithm / GraphCut algorithm / /

SocialTag