Learning shared body plans

Ian Endres, Vivek Srikumar, Ming Wei Chang, Derek Hoiem

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We cast the problem of recognizing related categories as a unified learning and structured prediction problem with shared body plans. When provided with detailed annotations of objects and their parts, these body plans model objects in terms of shared parts and layouts, simultaneously capturing a variety of categories in varied poses. We can use these body plans to jointly train many detectors in a shared framework with structured learning, leading to significant gains for each supervised task. Using our model, we can provide detailed predictions of objects and their parts for both familiar and unfamiliar categories.

Original languageEnglish (US)
Title of host publication2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012
Pages3130-3137
Number of pages8
DOIs
StatePublished - Oct 1 2012
Event2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012 - Providence, RI, United States
Duration: Jun 16 2012Jun 21 2012

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

Other

Other2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012
CountryUnited States
CityProvidence, RI
Period6/16/126/21/12

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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  • Cite this

    Endres, I., Srikumar, V., Chang, M. W., & Hoiem, D. (2012). Learning shared body plans. In 2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012 (pp. 3130-3137). [6248046] (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). https://doi.org/10.1109/CVPR.2012.6248046