Finding distractors in images

Ohad Fried, Eli Shechtman, Dan B. Goldman, Adam Finkelstein

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

10 Scopus citations

Abstract

We propose a new computer vision task we call 'distractor prediction.' Distractors are the regions of an image that draw attention away from the main subjects and reduce the overall image quality. Removing distractors - for example, using in-painting - can improve the composition of an image. In this work we created two datasets of images with user annotations to identify the characteristics of distractors. We use these datasets to train an algorithm to predict distractor maps. Finally, we use our predictor to automatically enhance images.

Original languageEnglish (US)
Title of host publicationIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
PublisherIEEE Computer Society
Pages1703-1712
Number of pages10
ISBN (Electronic)9781467369640
DOIs
StatePublished - Oct 14 2015
EventIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015 - Boston, United States
Duration: Jun 7 2015Jun 12 2015

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume07-12-June-2015
ISSN (Print)1063-6919

Other

OtherIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
CountryUnited States
CityBoston
Period6/7/156/12/15

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition

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  • Cite this

    Fried, O., Shechtman, E., Goldman, D. B., & Finkelstein, A. (2015). Finding distractors in images. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015 (pp. 1703-1712). [7298779] (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Vol. 07-12-June-2015). IEEE Computer Society. https://doi.org/10.1109/CVPR.2015.7298779