Attribute Dominance: What Pops Out?

Naman Turakhia, Devi Parikh; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2013, pp. 1225-1232


When we look at an image, some properties or attributes of the image stand out more than others. When describing an image, people are likely to describe these dominant attributes first. Attribute dominance is a result of a complex interplay between the various properties present or absent in the image. Which attributes in an image are more dominant than others reveals rich information about the content of the image. In this paper we tap into this information by modeling attribute dominance. We show that this helps improve the performance of vision systems on a variety of human-centric applications such as zero-shot learning, image search and generating textual descriptions of images.

Related Material

author = {Turakhia, Naman and Parikh, Devi},
title = {Attribute Dominance: What Pops Out?},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
month = {December},
year = {2013}