Learning Shared Body Plans

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

CVPR 2012 pp. 3130-3137

doi:10.1109/CVPR.2012.6248046 /cvpr/2012/endres2012cvpr-learning/

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.

CVPR Semantic Scholar

Cite

Text

Endres et al. "Learning Shared Body Plans." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2012. doi:10.1109/CVPR.2012.6248046

Markdown

[Endres et al. "Learning Shared Body Plans." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2012.](https://mlanthology.org/cvpr/2012/endres2012cvpr-learning/) doi:10.1109/CVPR.2012.6248046

BibTeX

@inproceedings{endres2012cvpr-learning,
  title     = {{Learning Shared Body Plans}},
  author    = {Endres, Ian and Srikumar, Vivek and Chang, Ming-Wei and Hoiem, Derek},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2012},
  pages     = {3130-3137},
  doi       = {10.1109/CVPR.2012.6248046},
  url       = {https://mlanthology.org/cvpr/2012/endres2012cvpr-learning/}
}